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提交 733d3109 编写于 作者: P phlrain
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update; test=develop

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Showing with 502 addition and 249 deletion
paddle/fluid/eager/auto_code_generator/final_state_generator/eager_gen.py
浏览文件 @ 733d3109
......@@ -687,6 +687,7 @@ def GenerateNodeCreationCodes(
pass_stop_gradient_args_list = ["false"]
num_fwd_outputs = len(forward_outputs_position_map.keys())
for name, (rtype, pos) in forward_outputs_position_map.items():
print("@@@@", fwd_api_name, name, rtype, pos)
output_autograd_meta_name = GetAutoGradMetaName(name)
output_autograd_meta_vec_name = GetAutoGradMetaVectorName(name)
if num_fwd_outputs == 1:
......@@ -727,19 +728,27 @@ def GenerateNodeCreationCodes(
# SetTensorWrappers
set_tensor_wrappers_list = []
fwd_api_input_num = 0
for name, (atype, is_fwd_input, pos) in backward_fwd_input_map.items():
is_optional = (name in optional_inputs)
if is_fwd_input:
fwd_api_input_num += 1
if is_optional:
set_tensor_wrappers = f" if({name}.is_initialized()) grad_node->SetTensorWrapper{name}({name}, true);"
else:
set_tensor_wrappers = f" grad_node->SetTensorWrapper{name}({name}, true);"
else:
print("!!!!", fwd_api_name, name, atype, pos)
if num_fwd_outputs == 1:
if IsVectorTensorType(atype):
tw_name = f"api_result[{pos}]"
tw_name = f"std::get<{pos}>(api_result)"
else:
tw_name = f"api_result"
else:
assert IsPlainTensorType(atype), atype
out_pos = pos - fwd_api_input_num
tw_name = f"std::get<{out_pos}>(api_result)"
if is_optional:
set_tensor_wrappers = f" if({tw_name}.is_initialized()) grad_node->SetTensorWrapper{name}({tw_name}, false);"
......@@ -779,7 +788,7 @@ def GenerateNodeCreationCodes(
if num_outputs == 1:
set_retain_grad = f" egr::EagerUtils::CheckAndRetainGrad(api_result);"
else:
set_retain_grad = f" egr::EagerUtils::CheckAndRetainGrad(api_result[{pos}]);"
set_retain_grad = f" egr::EagerUtils::CheckAndRetainGrad(std::get<{pos}>(api_result));"
set_retain_grad_list.append(set_retain_grad)
set_out_rank_str = "\n".join(set_out_rank_list)
set_history_str = "\n".join(set_history_list)
......@@ -902,7 +911,7 @@ def GenerateForwardDefinition(fwd_api_name, bwd_api_name,
returns_list[0] = f"api_result"
else:
# Tuple api_result
returns_list[pos] = f"api_result[{pos}]"
returns_list[pos] = f"std::get<{pos}>(api_result)"
if IsPlainTensorType(rtype):
returns_type_list[pos] = "paddle::experimental::Tensor"
......
paddle/fluid/eager/auto_code_generator/final_state_generator/python_c_gen.py
浏览文件 @ 733d3109
......@@ -22,7 +22,7 @@ atype_to_parsing_function = {
"bool": "CastPyArg2Boolean",
"int": "CastPyArg2Int",
"long": "CastPyArg2Long",
"std::string": "CastPyArgs2String",
"std::string": "CastPyArg2String",
"int64_t": "CastPyArg2Long",
"float": "CastPyArg2Float",
"string": "CastPyArg2String",
......
paddle/fluid/pybind/eager_utils.cc
浏览文件 @ 733d3109
......@@ -825,7 +825,7 @@ paddle::experimental::ScalarArray CastPyArg2ScalarArray(
// obj could be: int, float, bool, paddle.Tensor
PyTypeObject* type = obj->ob_type;
auto type_name = std::string(type->tp_name);
if (type_name == "list") {
if (type_name == "list" || type_name == "tuple") {
std::vector<int> value = CastPyArg2Ints(obj, op_type, arg_pos);
return paddle::experimental::ScalarArray(value);
......
paddle/phi/kernels/cpu/accuracy_kernel.cc
浏览文件 @ 733d3109
......@@ -69,4 +69,7 @@ void AccuracyRawKernel(const Context& dev_ctx,
// TODO(add supported dtype.)
PD_REGISTER_KERNEL(
accuracy, CPU, ALL_LAYOUT, phi::AccuracyRawKernel, float, double) {}
accuracy, CPU, ALL_LAYOUT, phi::AccuracyRawKernel, float, double) {
kernel->InputAt(1).SetDataType(phi::DataType::INT64);
kernel->InputAt(2).SetDataType(phi::DataType::INT64);
}
paddle/phi/kernels/cpu/put_along_axis_kernel.cc
浏览文件 @ 733d3109
......@@ -84,4 +84,6 @@ PD_REGISTER_KERNEL(put_along_axis,
double,
int,
uint8_t,
int64_t) {}
int64_t) {
kernel->InputAt(1).SetDataType(phi::DataType::ALL_DTYPE);
}
paddle/phi/kernels/cpu/take_along_axis_kernel.cc
浏览文件 @ 733d3109
......@@ -57,4 +57,6 @@ PD_REGISTER_KERNEL(take_along_axis,
double,
int,
uint8_t,
int64_t) {}
int64_t) {
kernel->InputAt(1).SetDataType(phi::DataType::ALL_DTYPE);
}
paddle/phi/kernels/gpu/accuracy_kernel.cu
浏览文件 @ 733d3109
......@@ -114,4 +114,7 @@ PD_REGISTER_KERNEL(accuracy,
phi::AccuracyRawKernel,
phi::dtype::float16,
float,
double) {}
double) {
kernel->InputAt(1).SetDataType(phi::DataType::INT64);
kernel->InputAt(2).SetDataType(phi::DataType::INT64);
}
paddle/phi/kernels/gpu/put_along_axis_kernel.cu
浏览文件 @ 733d3109
......@@ -83,4 +83,6 @@ PD_REGISTER_KERNEL(put_along_axis,
double,
int64_t,
int,
phi::dtype::float16) {}
phi::dtype::float16) {
kernel->InputAt(1).SetDataType(phi::DataType::ALL_DTYPE);
}
paddle/phi/kernels/gpu/take_along_axis_kernel.cu
浏览文件 @ 733d3109
......@@ -57,4 +57,6 @@ PD_REGISTER_KERNEL(take_along_axis,
double,
int64_t,
int,
phi::dtype::float16) {}
phi::dtype::float16) {
kernel->InputAt(1).SetDataType(phi::DataType::ALL_DTYPE);
}
paddle/phi/kernels/norm_grad_kernel.h
浏览文件 @ 733d3109
......@@ -21,7 +21,7 @@ namespace phi {
template <typename T, typename Context>
void NormGradKernel(const Context& ctx,
const DenseTensor& x,
const DenseTensor& out,
const DenseTensor& norm,
const DenseTensor& out_grad,
int axis,
float epsilon,
......
python/paddle/fluid/layers/control_flow.py
浏览文件 @ 733d3109
......@@ -18,7 +18,7 @@ from ..wrapped_decorator import signature_safe_contextmanager
from .layer_function_generator import autodoc, templatedoc
from .tensor import assign, cast, fill_constant
from .. import core
from ..framework import Program, Variable, Operator, in_dygraph_mode, static_only
from ..framework import Program, Variable, Operator, in_dygraph_mode, static_only, _in_eager_mode
from ..layer_helper import LayerHelper, unique_name
from .nn import logical_and, logical_not, logical_or
from .utils import assert_same_structure, map_structure, hold_mutable_vars, copy_mutable_vars
......@@ -3852,6 +3852,8 @@ def is_empty(x, name=None):
"""
if in_dygraph_mode():
if _in_eager_mode():
return _C_ops.final_state_is_empty(x)
return _C_ops.is_empty(x)
check_variable_and_dtype(x, 'x', ['float32', 'float64', 'int32', 'int64'],
......
python/paddle/fluid/layers/layer_function_generator.py
浏览文件 @ 733d3109
......@@ -258,6 +258,9 @@ def generate_activation_fn(op_type):
def func(x, name=None):
if in_dygraph_mode():
if _in_eager_mode():
op = getattr(_C_ops, "final_state_" + op_type)
return op(x)
op = getattr(_C_ops, op_type)
return op(x)
......
python/paddle/fluid/layers/loss.py
浏览文件 @ 733d3109
......@@ -1458,6 +1458,10 @@ def sigmoid_cross_entropy_with_logits(x,
ignore_index=-1, normalize=True)
print(loss)
"""
if in_dygraph_mode() and _in_eager_mode():
return _C_ops.final_state_sigmoid_cross_entropy_with_logits(
x, label, normalize, ignore_index)
check_variable_and_dtype(x, 'input', ['float16', 'float32', 'float64'],
'sigmoid_cross_entropy_with_logits')
......
python/paddle/fluid/layers/nn.py
浏览文件 @ 733d3109
......@@ -11571,6 +11571,8 @@ def size(input):
"""
if in_dygraph_mode():
if _in_eager_mode():
return _C_ops.final_state_size(input)
return _C_ops.size(input)
check_variable_and_dtype(
input, 'input',
......@@ -12543,7 +12545,8 @@ def logical_not(x, out=None, name=None):
res = paddle.logical_not(x)
print(res) # [False True False True]
"""
if paddle.in_dygraph_mode() and _in_eager_mode():
return _C_ops.final_state_logical_not(x)
return _logical_op(
op_name="logical_not", x=x, y=None, name=name, out=out, binary_op=False)
......@@ -13319,6 +13322,9 @@ def log_loss(input, label, epsilon=1e-4, name=None):
prob = paddle.randn((10,1))
cost = F.log_loss(input=prob, label=label)
"""
if in_dygraph_mode() and _in_eager_mode():
return _C_ops.final_state_log_loss(input, label, epsilon)
helper = LayerHelper('log_loss', **locals())
check_variable_and_dtype(input, 'input', ['float32'], 'log_loss')
check_variable_and_dtype(label, 'label', ['float32'], 'log_loss')
......@@ -14335,6 +14341,8 @@ def where(condition):
"""
if in_dygraph_mode():
if _in_eager_mode():
return _C_ops.final_state_where_index(condition)
return _C_ops.where_index(condition)
helper = LayerHelper("where_index", **locals())
......@@ -14829,8 +14837,8 @@ def unfold(x, kernel_sizes, strides=1, paddings=0, dilations=1, name=None):
if in_dygraph_mode():
if _in_eager_mode():
return _C_op.final_state_unfold(x, kernel_sizes, strdides, paddings,
dilations)
return _C_ops.final_state_unfold(x, kernel_sizes, strdides,
paddings, dilations)
out = helper.create_variable_for_type_inference(dtype=x.dtype)
helper.append_op(
......@@ -15059,6 +15067,10 @@ def shard_index(input, index_num, nshards, shard_id, ignore_value=-1):
print(shard_label)
# [[-1], [1]]
"""
if in_dygraph_mode() and _in_eager_mode():
return _C_ops.final_state_shard_index(input, index_num, nshards,
shard_id, ignore_value)
check_variable_and_dtype(input, 'input', ['int64', 'int32'], 'shard_index')
op_type = 'shard_index'
helper = LayerHelper(op_type, **locals())
......
python/paddle/fluid/layers/ops.py
浏览文件 @ 733d3109
......@@ -16,9 +16,10 @@ from __future__ import print_function
import os
from .layer_function_generator import generate_layer_fn, generate_activation_fn, generate_inplace_fn, add_sample_code
from .. import core
from ..framework import convert_np_dtype_to_dtype_, Variable
from ..framework import convert_np_dtype_to_dtype_, Variable, in_dygraph_mode, _in_eager_mode
from ..data_feeder import convert_dtype, check_variable_and_dtype, check_type, check_dtype
from paddle.utils import deprecated
from paddle import _C_ops
__deprecated_func_name__ = {
'tanh_shrink': 'tanhshrink',
......@@ -794,6 +795,10 @@ _erf_ = generate_layer_fn('erf')
def erf(x, name=None):
if in_dygraph_mode():
if _in_eager_mode():
return _C_ops.final_state_erf(x)
locals_var = locals().copy()
kwargs = dict()
for name, val in locals_var.items():
......
python/paddle/fluid/tests/unittests/op_test.py
浏览文件 @ 733d3109
......@@ -545,7 +545,6 @@ class OpTest(unittest.TestCase):
v.value().get_tensor().set_recursive_sequence_lengths(lod)
return v
else:
print("init her")
return paddle.to_tensor(value)
def get_sequence_batch_size_1_input(self, lod=None, shape=None):
......@@ -1502,7 +1501,7 @@ class OpTest(unittest.TestCase):
.recursive_sequence_lengths(), expect[1],
"Output (" + out_name + ") has different lod at " +
str(place) + " in eager dygraph mode")
if check_eager:
with fluid.dygraph.base.guard():
with _test_eager_guard():
self.assertListEqual(
eager_imperative_actual.value().get_tensor()
......
python/paddle/fluid/tests/unittests/test_accuracy_op.py
浏览文件 @ 733d3109
......@@ -20,6 +20,7 @@ from op_test import OpTest
import paddle
import paddle.fluid as fluid
from paddle.fluid import compiler, Program, program_guard
from paddle.fluid.framework import _test_eager_guard
class TestAccuracyOp(OpTest):
......@@ -49,7 +50,7 @@ class TestAccuracyOp(OpTest):
pass
def test_check_output(self):
self.check_output(check_eager=False)
self.check_output(check_eager=True)
class TestAccuracyOpFp16(TestAccuracyOp):
......@@ -57,7 +58,7 @@ class TestAccuracyOpFp16(TestAccuracyOp):
self.dtype = np.float16
def test_check_output(self):
self.check_output(atol=1e-3)
self.check_output(atol=1e-3, check_eager=True)
class TestAccuracyOpError(unittest.TestCase):
......@@ -127,6 +128,17 @@ class TestAccuracyAPI(unittest.TestCase):
self.assertEqual((result.numpy() == expect_value).all(), True)
with _test_eager_guard():
predictions = paddle.to_tensor(
[[0.2, 0.1, 0.4, 0.1, 0.1], [0.2, 0.3, 0.1, 0.15, 0.25]],
dtype='float32')
label = paddle.to_tensor([[2], [0]], dtype="int64")
result = paddle.metric.accuracy(
input=predictions, label=label, k=1)
expect_value = np.array([0.5], dtype='float32')
self.assertEqual((result.numpy() == expect_value).all(), True)
if __name__ == '__main__':
paddle.enable_static()
......
python/paddle/fluid/tests/unittests/test_activation_op.py
浏览文件 @ 733d3109
......@@ -59,12 +59,17 @@ class TestActivation(OpTest):
self.outputs = {'Out': out}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=(hasattr(self, "python_api") and
self.python_api != None))
def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(['X'], 'Out')
self.check_grad(
['X'],
'Out',
check_eager=(hasattr(self, "python_api") and
self.python_api != None))
def init_dtype(self):
self.dtype = np.float64
......@@ -356,6 +361,7 @@ class TestTanh(TestActivation, TestParameter):
def setUp(self):
self.op_type = "tanh"
self.init_dtype()
self.python_api = paddle.tanh
np.random.seed(1024)
x = np.random.uniform(0.1, 1, [11, 17]).astype(self.dtype)
out = np.tanh(x)
......@@ -366,7 +372,7 @@ class TestTanh(TestActivation, TestParameter):
def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
def init_dtype(self):
#TODO If dtype is float64, the output (Out) has diff at CPUPlace
......@@ -449,6 +455,7 @@ class TestAtan(TestActivation, TestParameter):
self.op_type = "atan"
self.init_dtype()
self.python_api = paddle.atan
np.random.seed(1024)
x = np.random.uniform(0.1, 1, [11, 17]).astype(self.dtype)
out = np.arctan(x)
......@@ -459,7 +466,7 @@ class TestAtan(TestActivation, TestParameter):
def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
def test_out_name(self):
with fluid.program_guard(fluid.Program()):
......@@ -485,6 +492,7 @@ class TestSinh(TestActivation):
def setUp(self):
self.op_type = "sinh"
self.init_dtype()
self.python_api = paddle.sinh
np.random.seed(1024)
x = np.random.uniform(0.1, 1, [11, 17]).astype(self.dtype)
......@@ -496,7 +504,7 @@ class TestSinh(TestActivation):
def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
def test_dygraph(self):
with fluid.dygraph.guard():
......@@ -557,6 +565,7 @@ class TestCosh(TestActivation):
def setUp(self):
self.op_type = "cosh"
self.init_dtype()
self.python_api = paddle.cosh
np.random.seed(1024)
x = np.random.uniform(0.1, 1, [11, 17]).astype(self.dtype)
......@@ -568,7 +577,7 @@ class TestCosh(TestActivation):
def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
def test_dygraph(self):
with fluid.dygraph.guard():
......@@ -1082,6 +1091,7 @@ class TestCos(TestActivation):
def setUp(self):
self.op_type = "cos"
self.init_dtype()
self.python_api = paddle.cos
np.random.seed(1024)
x = np.random.uniform(-1, 1, [10, 12]).astype(self.dtype)
......@@ -1093,7 +1103,7 @@ class TestCos(TestActivation):
def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
class TestTan(TestActivation):
......@@ -1151,6 +1161,7 @@ class TestAcos(TestActivation):
def setUp(self):
self.op_type = "acos"
self.init_dtype()
self.python_api = paddle.acos
np.random.seed(1024)
x = np.random.uniform(-0.95, 0.95, [10, 12]).astype(self.dtype)
......@@ -1162,13 +1173,14 @@ class TestAcos(TestActivation):
def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
class TestSin(TestActivation, TestParameter):
def setUp(self):
self.op_type = "sin"
self.init_dtype()
self.python_api = paddle.sin
np.random.seed(1024)
x = np.random.uniform(-1, 1, [10, 12]).astype(self.dtype)
......@@ -1180,13 +1192,14 @@ class TestSin(TestActivation, TestParameter):
def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
class TestAsin(TestActivation):
def setUp(self):
self.op_type = "asin"
self.init_dtype()
self.python_api = paddle.asin
np.random.seed(2048)
x = np.random.uniform(-0.95, 0.95, [10, 12]).astype(self.dtype)
......@@ -1198,13 +1211,14 @@ class TestAsin(TestActivation):
def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
class TestAcosh(TestActivation):
def setUp(self):
self.op_type = "acosh"
self.init_dtype()
self.python_api = paddle.acosh
np.random.seed(1024)
x = np.random.uniform(2, 3, [10, 12]).astype(self.dtype)
......@@ -1216,13 +1230,14 @@ class TestAcosh(TestActivation):
def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
class TestAsinh(TestActivation):
def setUp(self):
self.op_type = "asinh"
self.init_dtype()
self.python_api = paddle.asinh
np.random.seed(1024)
x = np.random.uniform(1, 2, [10, 12]).astype(self.dtype)
......@@ -1234,13 +1249,14 @@ class TestAsinh(TestActivation):
def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
class TestAtanh(TestActivation):
def setUp(self):
self.op_type = "atanh"
self.init_dtype()
self.python_api = paddle.atanh
np.random.seed(400)
x = np.random.uniform(-0.9, 0.9, [10, 12]).astype(self.dtype)
......@@ -1252,7 +1268,7 @@ class TestAtanh(TestActivation):
def test_check_grad(self):
if self.dtype == np.float16:
return
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
class TestRound(TestActivation):
......@@ -3195,4 +3211,5 @@ def create_test_act_bf16_class(parent,
create_test_act_bf16_class(TestRelu)
if __name__ == "__main__":
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_bernoulli_op.py
浏览文件 @ 733d3109
......@@ -19,6 +19,7 @@ import paddle
from op_test import OpTest
import numpy as np
import os
from paddle.fluid.framework import _test_eager_guard
def output_hist(out):
......@@ -32,6 +33,7 @@ def output_hist(out):
class TestBernoulliOp(OpTest):
def setUp(self):
self.op_type = "bernoulli"
self.python_api = paddle.bernoulli
self.inputs = {"X": np.random.uniform(size=(1000, 784))}
self.attrs = {}
self.outputs = {"Out": np.zeros((1000, 784)).astype("float32")}
......@@ -104,8 +106,28 @@ class TestRandomValue(unittest.TestCase):
expect = [0., 0., 1., 1., 1., 1., 0., 1., 1., 1.]
self.assertTrue(np.array_equal(y[16, 500, 500:510], expect))
with _test_eager_guard():
x = paddle.to_tensor(x_np, dtype='float64')
y = paddle.bernoulli(x).numpy()
index0, index1, index2 = np.nonzero(y)
self.assertEqual(np.sum(index0), 260028995)
self.assertEqual(np.sum(index1), 8582429431)
self.assertEqual(np.sum(index2), 8581445798)
expect = [0., 0., 0., 0., 0., 0., 0., 1., 1., 1.]
self.assertTrue(np.array_equal(y[16, 500, 500:510], expect))
x = paddle.to_tensor(x_np, dtype='float32')
y = paddle.bernoulli(x).numpy()
index0, index1, index2 = np.nonzero(y)
self.assertEqual(np.sum(index0), 260092343)
self.assertEqual(np.sum(index1), 8583509076)
self.assertEqual(np.sum(index2), 8582778540)
expect = [0., 0., 1., 1., 1., 1., 0., 1., 1., 1.]
self.assertTrue(np.array_equal(y[16, 500, 500:510], expect))
paddle.enable_static()
if __name__ == "__main__":
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_bincount_op.py
浏览文件 @ 733d3109
......@@ -20,6 +20,7 @@ import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
from paddle.fluid import Program, program_guard
from paddle.fluid.framework import _test_eager_guard
from op_test import OpTest
paddle.enable_static()
......@@ -62,6 +63,14 @@ class TestBincountOpAPI(unittest.TestCase):
(actual.numpy() == expected).all(),
msg='bincount output is wrong, out =' + str(actual.numpy()))
with _test_eager_guard():
inputs = fluid.dygraph.to_variable(inputs_np)
actual = paddle.bincount(inputs)
expected = np.bincount(inputs)
self.assertTrue(
(actual.numpy() == expected).all(),
msg='bincount output is wrong, out =' + str(actual.numpy()))
class TestBincountOpError(unittest.TestCase):
"""Test bincount op error."""
......
python/paddle/fluid/tests/unittests/test_bitwise_op.py
浏览文件 @ 733d3109
......@@ -289,7 +289,7 @@ class TestBitwiseNot(OpTest):
self.outputs = {'Out': out}
def test_check_output(self):
self.check_output(check_eager=False)
self.check_output(check_eager=True)
def test_check_grad(self):
pass
......
python/paddle/fluid/tests/unittests/test_cholesky_solve_op.py
浏览文件 @ 733d3109
......@@ -128,132 +128,135 @@ class TestCholeskySolveOp(OpTest):
def test_check_output(self):
self.check_output(check_eager=True)
# def test_check_grad_normal(self):
# self.check_grad(['Y'], 'Out', max_relative_error=0.01, check_eager=True)
# # 3D(broadcast) + 3D, upper=True
# class TestCholeskySolveOp3(TestCholeskySolveOp):
# """
# case 3
# """
# def config(self):
# self.y_shape = [1, 10, 10]
# self.x_shape = [2, 10, 5]
# self.upper = True
# self.dtype = np.float64
# class TestCholeskySolveAPI(unittest.TestCase):
# def setUp(self):
# np.random.seed(2021)
# self.place = [paddle.CPUPlace()]
# # self.place = [paddle.CUDAPlace(0)]
# self.dtype = "float64"
# self.upper = True
# if core.is_compiled_with_cuda():
# self.place.append(paddle.CUDAPlace(0))
# def check_static_result(self, place):
# paddle.enable_static()
# with fluid.program_guard(fluid.Program(), fluid.Program()):
# x = fluid.data(name="x", shape=[10, 2], dtype=self.dtype)
# y = fluid.data(name="y", shape=[10, 10], dtype=self.dtype)
# z = paddle.linalg.cholesky_solve(x, y, upper=self.upper)
# x_np = np.random.random([10, 2]).astype(self.dtype)
# y_np = np.random.random([10, 10]).astype(self.dtype)
# if self.upper:
# umat = np.triu(y_np)
# else:
# umat = np.tril(y_np)
# z_np = cholesky_solution(umat, x_np, upper=self.upper)
# z2_np = scipy_cholesky_solution(umat, x_np, upper=self.upper)
# exe = fluid.Executor(place)
# fetches = exe.run(fluid.default_main_program(),
# feed={"x": x_np,
# "y": umat},
# fetch_list=[z])
# self.assertTrue(np.allclose(fetches[0], z_np))
# def test_static(self):
# for place in self.place:
# self.check_static_result(place=place)
# def test_dygraph(self):
# def run(place):
# paddle.disable_static(place)
# x_np = np.random.random([20, 2]).astype(self.dtype)
# y_np = np.random.random([20, 20]).astype(self.dtype)
# z_np = scipy_cholesky_solution(y_np, x_np, upper=self.upper)
# x = paddle.to_tensor(x_np)
# y = paddle.to_tensor(y_np)
# z = paddle.linalg.cholesky_solve(x, y, upper=self.upper)
# self.assertTrue(np.allclose(z_np, z.numpy()))
# self.assertEqual(z_np.shape, z.numpy().shape)
# paddle.enable_static()
# for idx, place in enumerate(self.place):
# run(place)
# def test_boardcast(self):
# def run(place):
# paddle.disable_static()
# x_np = np.random.random([1, 30, 2]).astype(self.dtype)
# y_np = np.random.random([2, 30, 30]).astype(self.dtype)
# nx_np = np.concatenate((x_np, x_np), axis=0)
# z_sci = scipy_cholesky_solution_batch(y_np, nx_np, upper=self.upper)
# x = paddle.to_tensor(x_np)
# y = paddle.to_tensor(y_np)
# z = paddle.linalg.cholesky_solve(x, y, upper=self.upper)
# self.assertEqual(z_sci.shape, z.numpy().shape)
# self.assertTrue(np.allclose(z_sci, z.numpy()))
# for idx, place in enumerate(self.place):
# run(place)
# class TestCholeskySolveOpError(unittest.TestCase):
# def test_errors(self):
# paddle.enable_static()
# with program_guard(Program(), Program()):
# # The input type of solve_op must be Variable.
# x1 = fluid.create_lod_tensor(
# np.array([[-1]]), [[1]], fluid.CPUPlace())
# y1 = fluid.create_lod_tensor(
# np.array([[-1]]), [[1]], fluid.CPUPlace())
# self.assertRaises(TypeError, paddle.linalg.cholesky_solve, x1, y1)
# # The data type of input must be float32 or float64.
# x2 = fluid.data(name="x2", shape=[30, 30], dtype="bool")
# y2 = fluid.data(name="y2", shape=[30, 10], dtype="bool")
# self.assertRaises(TypeError, paddle.linalg.cholesky_solve, x2, y2)
# x3 = fluid.data(name="x3", shape=[30, 30], dtype="int32")
# y3 = fluid.data(name="y3", shape=[30, 10], dtype="int32")
# self.assertRaises(TypeError, paddle.linalg.cholesky_solve, x3, y3)
# x4 = fluid.data(name="x4", shape=[30, 30], dtype="float16")
# y4 = fluid.data(name="y4", shape=[30, 10], dtype="float16")
# self.assertRaises(TypeError, paddle.linalg.cholesky_solve, x4, y4)
# # The number of dimensions of input'X must be >= 2.
# x5 = fluid.data(name="x5", shape=[30], dtype="float64")
# y5 = fluid.data(name="y5", shape=[30, 30], dtype="float64")
# self.assertRaises(ValueError, paddle.linalg.cholesky_solve, x5, y5)
# # The number of dimensions of input'Y must be >= 2.
# x6 = fluid.data(name="x6", shape=[30, 30], dtype="float64")
# y6 = fluid.data(name="y6", shape=[30], dtype="float64")
# self.assertRaises(ValueError, paddle.linalg.cholesky_solve, x6, y6)
# # The inner-most 2 dimensions of input'X should be equal to each other
# x7 = fluid.data(name="x7", shape=[2, 3, 4], dtype="float64")
# y7 = fluid.data(name="y7", shape=[2, 4, 3], dtype="float64")
# self.assertRaises(ValueError, paddle.linalg.cholesky_solve, x7, y7)
def test_check_grad_normal(self):
self.check_grad(['Y'], 'Out', max_relative_error=0.01, check_eager=True)
# 3D(broadcast) + 3D, upper=True
class TestCholeskySolveOp3(TestCholeskySolveOp):
"""
case 3
"""
def config(self):
self.y_shape = [1, 10, 10]
self.x_shape = [2, 10, 5]
self.upper = True
self.dtype = np.float64
class TestCholeskySolveAPI(unittest.TestCase):
def setUp(self):
np.random.seed(2021)
self.place = [paddle.CPUPlace()]
# self.place = [paddle.CUDAPlace(0)]
self.dtype = "float64"
self.upper = True
if core.is_compiled_with_cuda():
self.place.append(paddle.CUDAPlace(0))
def check_static_result(self, place):
paddle.enable_static()
with fluid.program_guard(fluid.Program(), fluid.Program()):
x = fluid.data(name="x", shape=[10, 2], dtype=self.dtype)
y = fluid.data(name="y", shape=[10, 10], dtype=self.dtype)
z = paddle.linalg.cholesky_solve(x, y, upper=self.upper)
x_np = np.random.random([10, 2]).astype(self.dtype)
y_np = np.random.random([10, 10]).astype(self.dtype)
if self.upper:
umat = np.triu(y_np)
else:
umat = np.tril(y_np)
z_np = cholesky_solution(umat, x_np, upper=self.upper)
z2_np = scipy_cholesky_solution(umat, x_np, upper=self.upper)
exe = fluid.Executor(place)
fetches = exe.run(fluid.default_main_program(),
feed={"x": x_np,
"y": umat},
fetch_list=[z])
self.assertTrue(np.allclose(fetches[0], z_np))
def test_static(self):
for place in self.place:
self.check_static_result(place=place)
def test_dygraph(self):
def run(place):
paddle.disable_static(place)
x_np = np.random.random([20, 2]).astype(self.dtype)
y_np = np.random.random([20, 20]).astype(self.dtype)
z_np = scipy_cholesky_solution(y_np, x_np, upper=self.upper)
x = paddle.to_tensor(x_np)
y = paddle.to_tensor(y_np)
z = paddle.linalg.cholesky_solve(x, y, upper=self.upper)
self.assertTrue(np.allclose(z_np, z.numpy()))
self.assertEqual(z_np.shape, z.numpy().shape)
paddle.enable_static()
for idx, place in enumerate(self.place):
run(place)
def test_boardcast(self):
def run(place):
paddle.disable_static()
x_np = np.random.random([1, 30, 2]).astype(self.dtype)
y_np = np.random.random([2, 30, 30]).astype(self.dtype)
nx_np = np.concatenate((x_np, x_np), axis=0)
z_sci = scipy_cholesky_solution_batch(y_np, nx_np, upper=self.upper)
x = paddle.to_tensor(x_np)
y = paddle.to_tensor(y_np)
z = paddle.linalg.cholesky_solve(x, y, upper=self.upper)
self.assertEqual(z_sci.shape, z.numpy().shape)
self.assertTrue(np.allclose(z_sci, z.numpy()))
for idx, place in enumerate(self.place):
run(place)
class TestCholeskySolveOpError(unittest.TestCase):
def test_errors(self):
paddle.enable_static()
with program_guard(Program(), Program()):
# The input type of solve_op must be Variable.
x1 = fluid.create_lod_tensor(
np.array([[-1]]), [[1]], fluid.CPUPlace())
y1 = fluid.create_lod_tensor(
np.array([[-1]]), [[1]], fluid.CPUPlace())
self.assertRaises(TypeError, paddle.linalg.cholesky_solve, x1, y1)
# The data type of input must be float32 or float64.
x2 = fluid.data(name="x2", shape=[30, 30], dtype="bool")
y2 = fluid.data(name="y2", shape=[30, 10], dtype="bool")
self.assertRaises(TypeError, paddle.linalg.cholesky_solve, x2, y2)
x3 = fluid.data(name="x3", shape=[30, 30], dtype="int32")
y3 = fluid.data(name="y3", shape=[30, 10], dtype="int32")
self.assertRaises(TypeError, paddle.linalg.cholesky_solve, x3, y3)
x4 = fluid.data(name="x4", shape=[30, 30], dtype="float16")
y4 = fluid.data(name="y4", shape=[30, 10], dtype="float16")
self.assertRaises(TypeError, paddle.linalg.cholesky_solve, x4, y4)
# The number of dimensions of input'X must be >= 2.
x5 = fluid.data(name="x5", shape=[30], dtype="float64")
y5 = fluid.data(name="y5", shape=[30, 30], dtype="float64")
self.assertRaises(ValueError, paddle.linalg.cholesky_solve, x5, y5)
# The number of dimensions of input'Y must be >= 2.
x6 = fluid.data(name="x6", shape=[30, 30], dtype="float64")
y6 = fluid.data(name="y6", shape=[30], dtype="float64")
self.assertRaises(ValueError, paddle.linalg.cholesky_solve, x6, y6)
# The inner-most 2 dimensions of input'X should be equal to each other
x7 = fluid.data(name="x7", shape=[2, 3, 4], dtype="float64")
y7 = fluid.data(name="y7", shape=[2, 4, 3], dtype="float64")
self.assertRaises(ValueError, paddle.linalg.cholesky_solve, x7, y7)
if __name__ == "__main__":
......
python/paddle/fluid/tests/unittests/test_cumsum_op.py
浏览文件 @ 733d3109
......@@ -21,6 +21,7 @@ import paddle
import paddle.fluid.core as core
import paddle.fluid as fluid
from paddle.fluid import compiler, Program, program_guard
from paddle.fluid.framework import _test_eager_guard
class TestCumsumOp(unittest.TestCase):
......@@ -84,6 +85,9 @@ class TestCumsumOp(unittest.TestCase):
def test_cpu(self):
paddle.disable_static(paddle.fluid.CPUPlace())
self.run_cases()
with _test_eager_guard():
self.run_cases()
paddle.enable_static()
self.run_static()
......@@ -107,15 +111,16 @@ class TestCumsumOp(unittest.TestCase):
class TestSumOp1(OpTest):
def setUp(self):
self.op_type = "cumsum"
self.python_api = paddle.cumsum
self.attrs = {'axis': 2}
self.inputs = {'X': np.random.random((5, 6, 10)).astype("float64")}
self.outputs = {'Out': self.inputs['X'].cumsum(axis=2)}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
def test_check_grad(self):
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
class TestSumOp2(OpTest):
......@@ -306,4 +311,5 @@ class BadInputTest(unittest.TestCase):
if __name__ == '__main__':
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_eigh_op.py
浏览文件 @ 733d3109
......@@ -25,6 +25,7 @@ class TestEighOp(OpTest):
def setUp(self):
paddle.enable_static()
self.op_type = "eigh"
self.python_api = paddle.linalg.eigh
self.init_input()
self.init_config()
np.random.seed(123)
......@@ -42,10 +43,10 @@ class TestEighOp(OpTest):
self.x_np = np.random.random(self.x_shape).astype(self.x_type)
def test_check_output(self):
self.check_output(no_check_set=['Eigenvectors'])
self.check_output(no_check_set=['Eigenvectors'], check_eager=True)
def test_grad(self):
self.check_grad(["X"], ["Eigenvalues"])
self.check_grad(["X"], ["Eigenvalues"], check_eager=True)
class TestEighUPLOCase(TestEighOp):
......@@ -207,4 +208,5 @@ class TestEighAPIError(unittest.TestCase):
if __name__ == "__main__":
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_erf_op.py
浏览文件 @ 733d3109
......@@ -27,6 +27,7 @@ import paddle.fluid.dygraph as dg
class TestErfOp(OpTest):
def setUp(self):
self.op_type = "erf"
self.python_api = paddle.erf
self.dtype = self._init_dtype()
self.x_shape = [11, 17]
x = np.random.uniform(-1, 1, size=self.x_shape).astype(self.dtype)
......@@ -38,10 +39,10 @@ class TestErfOp(OpTest):
return "float64"
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
def test_check_grad(self):
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
class TestErfLayer(unittest.TestCase):
......@@ -67,4 +68,5 @@ class TestErfLayer(unittest.TestCase):
if __name__ == '__main__':
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_erfinv_op.py
浏览文件 @ 733d3109
......@@ -21,13 +21,13 @@ from op_test import OpTest
import paddle
import paddle.fluid.core as core
paddle.enable_static()
np.random.seed(0)
class TestErfinv(OpTest):
def setUp(self):
self.op_type = "erfinv"
self.python_api = paddle.erfinv
self.init_dtype()
self.shape = [11, 17]
self.x = np.random.uniform(-1, 1, size=self.shape).astype(self.dtype)
......@@ -42,14 +42,15 @@ class TestErfinv(OpTest):
self.dtype = np.float64
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
def test_check_grad(self):
self.check_grad(
['X'],
'Out',
user_defined_grads=[self.gradient],
user_defined_grad_outputs=self.grad_out)
user_defined_grad_outputs=self.grad_out,
check_eager=True)
class TestErfinvFP32(TestErfinv):
......@@ -108,4 +109,5 @@ class TestErfinvAPI(unittest.TestCase):
if __name__ == "__main__":
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_increment.py
浏览文件 @ 733d3109
......@@ -19,6 +19,7 @@ import unittest
import numpy as np
import paddle
import paddle.fluid as fluid
from paddle.fluid.framework import _test_eager_guard
class TestIncrement(unittest.TestCase):
......@@ -39,6 +40,14 @@ class TestIncrement(unittest.TestCase):
output = paddle.tensor.math.increment(input, value=1)
self.assertEqual((output.numpy() == expected_result).all(), True)
with fluid.dygraph.guard():
with _test_eager_guard():
input = paddle.ones(shape=[1], dtype='int64')
expected_result = np.array([2], dtype='int64')
output = paddle.tensor.math.increment(input, value=1)
self.assertEqual((output.numpy() == expected_result).all(),
True)
class TestInplaceApiWithDataTransform(unittest.TestCase):
def test_increment(self):
......@@ -55,4 +64,5 @@ class TestInplaceApiWithDataTransform(unittest.TestCase):
if __name__ == "__main__":
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_is_empty_op.py
浏览文件 @ 733d3109
......@@ -23,11 +23,12 @@ import paddle
class TestEmpty(OpTest):
def setUp(self):
self.op_type = "is_empty"
self.python_api = paddle.is_empty
self.inputs = {'X': np.array([1, 2, 3])}
self.outputs = {'Out': np.array([False])}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
class TestNotEmpty(TestEmpty):
......@@ -75,4 +76,5 @@ class TestIsEmptyOpDygraph(unittest.TestCase):
if __name__ == "__main__":
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_log_loss_op.py
浏览文件 @ 733d3109
......@@ -18,6 +18,7 @@ import unittest
import numpy as np
from op_test import OpTest
import paddle.fluid as fluid
import paddle
def sigmoid_array(x):
......@@ -27,6 +28,7 @@ def sigmoid_array(x):
class TestLogLossOp(OpTest):
def setUp(self):
self.op_type = 'log_loss'
self.python_api = paddle.nn.functional.log_loss
samples_num = 100
x = np.random.random((samples_num, 1)).astype("float32")
......@@ -44,10 +46,11 @@ class TestLogLossOp(OpTest):
self.outputs = {'Loss': loss}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
def test_check_grad(self):
self.check_grad(['Predicted'], 'Loss', max_relative_error=0.03)
self.check_grad(
['Predicted'], 'Loss', max_relative_error=0.03, check_eager=True)
class TestLogLossOpError(unittest.TestCase):
......@@ -80,4 +83,5 @@ class TestLogLossOpError(unittest.TestCase):
if __name__ == '__main__':
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_matrix_power_op.py
浏览文件 @ 733d3109
......@@ -31,6 +31,7 @@ class TestMatrixPowerOp(OpTest):
def setUp(self):
self.op_type = "matrix_power"
self.config()
self.python_api = paddle.linalg.matrix_power
np.random.seed(123)
mat = np.random.random(self.matrix_shape).astype(self.dtype)
......@@ -41,11 +42,15 @@ class TestMatrixPowerOp(OpTest):
self.attrs = {"n": self.n}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
def test_grad(self):
self.check_grad(
["X"], "Out", numeric_grad_delta=1e-5, max_relative_error=1e-7)
["X"],
"Out",
numeric_grad_delta=1e-5,
max_relative_error=1e-7,
check_eager=True)
class TestMatrixPowerOpN1(TestMatrixPowerOp):
......
python/paddle/fluid/tests/unittests/test_multinomial_op.py
浏览文件 @ 733d3109
......@@ -20,6 +20,7 @@ import paddle.fluid as fluid
from paddle.fluid import core
from op_test import OpTest
import numpy as np
from paddle.fluid.framework import _test_eager_guard
def sample_output_one_dimension(out, dim):
......@@ -46,6 +47,7 @@ class TestMultinomialOp(OpTest):
def setUp(self):
paddle.enable_static()
self.op_type = "multinomial"
self.python_api = paddle.multinomial
self.init_data()
self.inputs = {"X": self.input_np}
......@@ -113,6 +115,22 @@ class TestMultinomialApi(unittest.TestCase):
sample_prob, prob, rtol=0, atol=0.01),
"sample_prob: " + str(sample_prob) + "\nprob: " + str(prob))
def test_eager(self):
# input probability is a vector, and replacement is True
paddle.disable_static()
with _test_eager_guard():
x_numpy = np.random.rand(4)
x = paddle.to_tensor(x_numpy)
out = paddle.multinomial(x, num_samples=100000, replacement=True)
sample_prob = sample_output_one_dimension(out.numpy(), 4)
prob = x_numpy / x_numpy.sum(axis=-1, keepdims=True)
self.assertTrue(
np.allclose(
sample_prob, prob, rtol=0, atol=0.01),
"sample_prob: " + str(sample_prob) + "\nprob: " + str(prob))
paddle.enable_static()
def test_dygraph2(self):
# input probability is a matrix, and replacement is True
paddle.disable_static()
......@@ -128,6 +146,22 @@ class TestMultinomialApi(unittest.TestCase):
"sample_prob: " + str(sample_prob) + "\nprob: " + str(prob))
paddle.enable_static()
def test_eager2(self):
# input probability is a matrix, and replacement is True
paddle.disable_static()
with _test_eager_guard():
x_numpy = np.random.rand(3, 4)
x = paddle.to_tensor(x_numpy)
out = paddle.multinomial(x, num_samples=100000, replacement=True)
sample_prob = sample_output_two_dimension(out.numpy(), [3, 4])
prob = x_numpy / x_numpy.sum(axis=-1, keepdims=True)
self.assertTrue(
np.allclose(
sample_prob, prob, rtol=0, atol=0.01),
"sample_prob: " + str(sample_prob) + "\nprob: " + str(prob))
paddle.enable_static()
def test_dygraph3(self):
# replacement is False. number of samples must be less than number of categories.
paddle.disable_static()
......@@ -217,4 +251,5 @@ class TestMultinomialError(unittest.TestCase):
if __name__ == "__main__":
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_segment_ops.py
浏览文件 @ 733d3109
......@@ -93,6 +93,7 @@ class TestSegmentOps(OpTest):
self.dtype = np.float64
self.shape = [30, 15]
self.attrs = {"pooltype": "SUM"}
self.python_api = paddle.incubate.segment_sum
def setUp(self):
self.prepare()
......@@ -105,10 +106,10 @@ class TestSegmentOps(OpTest):
self.outputs = {'Out': result.astype(self.dtype)}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=False)
def test_check_grad(self):
self.check_grad(["X"], "Out")
self.check_grad(["X"], "Out", check_eager=False)
class TestSegmentSum2(TestSegmentOps):
......@@ -136,6 +137,7 @@ class TestSegmentMax(TestSegmentOps):
super(TestSegmentMax, self).prepare()
self.shape = [40, 20]
self.attrs = {'pooltype': "MAX"}
# self.python_api = paddle.incubate.segment_max
def setUp(self):
self.prepare()
......@@ -148,7 +150,8 @@ class TestSegmentMax(TestSegmentOps):
self.outputs = {'Out': result.astype(self.dtype)}
def test_check_grad(self):
self.check_grad(["X"], "Out", user_defined_grads=[self.gradient])
self.check_grad(
["X"], "Out", user_defined_grads=[self.gradient], check_eager=False)
class TestSegmentMax2(TestSegmentMax):
......@@ -164,6 +167,7 @@ class TestSegmentMin(TestSegmentMax):
def prepare(self):
super(TestSegmentMin, self).prepare()
self.attrs = {'pooltype': "MIN"}
#self.python_api = paddle.incubate.segment_min
class TestSegmentMin2(TestSegmentMin):
......@@ -180,6 +184,7 @@ class TestSegmentMean(TestSegmentOps):
super(TestSegmentMean, self).prepare()
self.shape = [40, 20]
self.attrs = {'pooltype': "MEAN"}
#self.python_api = paddle.incubate.segment_mean
def setUp(self):
self.prepare()
......@@ -199,6 +204,7 @@ class TestSegmentMean2(TestSegmentMean):
self.dtype = np.float32
self.shape = [30, 20]
self.attrs = {'pooltype': "MEAN"}
#self.python_api = paddle.incubate.segment_mean
class API_SegmentOpsTest(unittest.TestCase):
......@@ -259,4 +265,5 @@ class API_SegmentOpsTest(unittest.TestCase):
if __name__ == '__main__':
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_selu_op.py
浏览文件 @ 733d3109
......@@ -24,6 +24,7 @@ import paddle.fluid as fluid
import paddle.nn as nn
import paddle.nn.functional as F
from paddle.fluid import compiler, Program, program_guard
from paddle.fluid.framework import _test_eager_guard
def ref_selu(x,
......@@ -113,6 +114,15 @@ class TestSeluAPI(unittest.TestCase):
out_ref = ref_selu(self.x_np, self.scale, self.alpha)
for r in [out1, out2]:
self.assertEqual(np.allclose(out_ref, r.numpy()), True)
with _test_eager_guard():
x = paddle.to_tensor(self.x_np)
out1 = F.selu(x, self.scale, self.alpha)
selu = paddle.nn.SELU(self.scale, self.alpha)
out2 = selu(x)
out_ref = ref_selu(self.x_np, self.scale, self.alpha)
for r in [out1, out2]:
self.assertEqual(np.allclose(out_ref, r.numpy()), True)
paddle.enable_static()
def test_fluid_api(self):
......@@ -145,4 +155,5 @@ class TestSeluAPI(unittest.TestCase):
if __name__ == "__main__":
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_shard_index_op.py
浏览文件 @ 733d3109
......@@ -22,10 +22,12 @@ import paddle.fluid as fluid
import paddle.fluid.core as core
import paddle.fluid.framework as framework
from paddle.fluid.framework import Program, program_guard
import paddle
def common_setup(self, index_num, nshards, shard_id, ignore_value):
self.op_type = 'shard_index'
self.python_api = paddle.shard_index
x_lod = [[i for i in range(10)]]
N = sum(x_lod[0])
x = [np.random.randint(0, index_num - 1) for i in range(N)]
......@@ -54,7 +56,7 @@ class TestShardIndexShardId0Op(OpTest):
common_setup(self, 20, 2, 0, -1)
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
class TestShardIndexShardId1Op(OpTest):
......@@ -62,7 +64,7 @@ class TestShardIndexShardId1Op(OpTest):
common_setup(self, 20, 2, 1, -1)
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
class TestShardIndexIgnoreValueOp(OpTest):
......@@ -70,7 +72,7 @@ class TestShardIndexIgnoreValueOp(OpTest):
common_setup(self, 20, 2, 0, -2)
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
class TestShardIndexNotEvenlyDividedOp(OpTest):
......@@ -78,8 +80,9 @@ class TestShardIndexNotEvenlyDividedOp(OpTest):
common_setup(self, 15, 2, 1, -1)
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
if __name__ == '__main__':
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_sigmoid_cross_entropy_with_logits_op.py
浏览文件 @ 733d3109
......@@ -22,6 +22,7 @@ import paddle.fluid.core as core
import unittest
from paddle.fluid import compiler, Program, program_guard
import paddle.fluid as fluid
import paddle
class TestSigmoidCrossEntropyWithLogitsOp1(OpTest):
......@@ -30,6 +31,7 @@ class TestSigmoidCrossEntropyWithLogitsOp1(OpTest):
def setUp(self):
self.op_type = "sigmoid_cross_entropy_with_logits"
self.python_api = paddle.fluid.layers.sigmoid_cross_entropy_with_logits
batch_size = 64
num_classes = 20
self.inputs = {
......@@ -49,10 +51,10 @@ class TestSigmoidCrossEntropyWithLogitsOp1(OpTest):
self.outputs = {'Out': -term1 - term2}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=False)
def test_check_grad(self):
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=False)
class TestSigmoidCrossEntropyWithLogitsOp2(OpTest):
......@@ -61,6 +63,7 @@ class TestSigmoidCrossEntropyWithLogitsOp2(OpTest):
def setUp(self):
self.op_type = "sigmoid_cross_entropy_with_logits"
self.python_api = paddle.fluid.layers.sigmoid_cross_entropy_with_logits
batch_size = 64
num_classes = 20
ignore_index = -1
......@@ -83,10 +86,10 @@ class TestSigmoidCrossEntropyWithLogitsOp2(OpTest):
self.outputs = {'Out': out}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=False)
def test_check_grad(self):
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=False)
class TestSigmoidCrossEntropyWithLogitsOp3(OpTest):
......@@ -95,6 +98,7 @@ class TestSigmoidCrossEntropyWithLogitsOp3(OpTest):
def setUp(self):
self.op_type = "sigmoid_cross_entropy_with_logits"
self.python_api = paddle.fluid.layers.sigmoid_cross_entropy_with_logits
batch_size = 64
num_classes = 20
self.inputs = {
......@@ -114,15 +118,16 @@ class TestSigmoidCrossEntropyWithLogitsOp3(OpTest):
self.outputs = {'Out': -term1 - term2}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=False)
def test_check_grad(self):
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=False)
class TestSigmoidCrossEntropyWithNorm(OpTest):
def setUp(self):
self.op_type = "sigmoid_cross_entropy_with_logits"
self.python_api = paddle.fluid.layers.sigmoid_cross_entropy_with_logits
batch_size = 64
num_classes = 20
ignore_index = -1
......@@ -145,10 +150,10 @@ class TestSigmoidCrossEntropyWithNorm(OpTest):
self.outputs = {'Out': out}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=False)
def test_check_grad(self):
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=False)
class TestSigmoidCrossEntropyWithLogitsOp5(OpTest):
......@@ -157,6 +162,7 @@ class TestSigmoidCrossEntropyWithLogitsOp5(OpTest):
def setUp(self):
self.op_type = "sigmoid_cross_entropy_with_logits"
self.python_api = paddle.fluid.layers.sigmoid_cross_entropy_with_logits
batch_size = [10, 10]
num_classes = 20
self.inputs = {
......@@ -176,15 +182,16 @@ class TestSigmoidCrossEntropyWithLogitsOp5(OpTest):
self.outputs = {'Out': -term1 - term2}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=False)
def test_check_grad(self):
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=False)
class TestSigmoidCrossEntropyWithNorm2(OpTest):
def setUp(self):
self.op_type = "sigmoid_cross_entropy_with_logits"
self.python_api = paddle.fluid.layers.sigmoid_cross_entropy_with_logits
batch_size = [10, 10]
num_classes = 20
ignore_index = -1
......@@ -207,10 +214,10 @@ class TestSigmoidCrossEntropyWithNorm2(OpTest):
self.outputs = {'Out': out}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=False)
def test_check_grad(self):
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=False)
class TestSigmoidCrossEntropyWithLogitsOp6(OpTest):
......@@ -219,6 +226,7 @@ class TestSigmoidCrossEntropyWithLogitsOp6(OpTest):
def setUp(self):
self.op_type = "sigmoid_cross_entropy_with_logits"
self.python_api = paddle.fluid.layers.sigmoid_cross_entropy_with_logits
batch_size = [10, 10]
num_classes = 20
self.inputs = {
......@@ -238,10 +246,10 @@ class TestSigmoidCrossEntropyWithLogitsOp6(OpTest):
self.outputs = {'Out': -term1 - term2}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=False)
def test_check_grad(self):
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=False)
class TestSigmoidCrossEntropyWithLogitsOpError(unittest.TestCase):
......@@ -271,4 +279,5 @@ class TestSigmoidCrossEntropyWithLogitsOpError(unittest.TestCase):
if __name__ == '__main__':
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_size_op.py
浏览文件 @ 733d3109
......@@ -22,6 +22,7 @@ from op_test import OpTest
class TestSizeOp(OpTest):
def setUp(self):
self.op_type = "size"
self.python_api = paddle.numel
self.shape = []
self.config()
input = np.zeros(self.shape, dtype='bool')
......@@ -32,7 +33,7 @@ class TestSizeOp(OpTest):
pass
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
class TestRank1Tensor(TestSizeOp):
......
python/paddle/fluid/tests/unittests/test_softmax_op.py
浏览文件 @ 733d3109
......@@ -85,10 +85,10 @@ class TestSoftmaxOp(OpTest):
place,
atol=1e-5,
check_dygraph=(self.use_mkldnn == False),
check_eager=False)
check_eager=True)
else:
self.check_output(
check_dygraph=(self.use_mkldnn == False), check_eager=False)
check_dygraph=(self.use_mkldnn == False), check_eager=True)
def test_check_grad(self):
# TODO(wangzhongpu): support mkldnn op in dygraph mode
......
python/paddle/fluid/tests/unittests/test_take_along_axis_op.py
浏览文件 @ 733d3109
......@@ -29,6 +29,7 @@ class TestTakeAlongAxisOp(OpTest):
def setUp(self):
self.init_data()
self.op_type = "take_along_axis"
self.python_api = paddle.take_along_axis
self.xnp = np.random.random(self.x_shape).astype(self.x_type)
self.target = np.take_along_axis(self.xnp, self.index, self.axis)
broadcast_shape_list = list(self.x_shape)
......@@ -43,10 +44,10 @@ class TestTakeAlongAxisOp(OpTest):
self.outputs = {'Result': self.target}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
def test_check_grad(self):
self.check_grad(['Input'], 'Result')
self.check_grad(['Input'], 'Result', check_eager=True)
def init_data(self):
self.x_type = "float64"
......
python/paddle/fluid/tests/unittests/test_tile_op.py
浏览文件 @ 733d3109
......@@ -27,6 +27,7 @@ class TestTileOpRank1(OpTest):
def setUp(self):
self.op_type = "tile"
self.init_data()
self.python_api = paddle.tile
self.inputs = {'X': np.random.random(self.ori_shape).astype("float64")}
self.attrs = {'repeat_times': self.repeat_times}
......@@ -38,10 +39,10 @@ class TestTileOpRank1(OpTest):
self.repeat_times = [2]
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
def test_check_grad(self):
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_eager=True)
# with dimension expanding
......@@ -85,6 +86,7 @@ class TestTileOpRank4(TestTileOpRank1):
class TestTileOpRank1_tensor_attr(OpTest):
def setUp(self):
self.op_type = "tile"
self.python_api = paddle.tile
self.init_data()
repeat_times_tensor = []
for index, ele in enumerate(self.repeat_times):
......@@ -160,6 +162,7 @@ class TestTileOpRank2_tensor(TestTileOpRank1_tensor):
class TestTileOpInteger(OpTest):
def setUp(self):
self.op_type = "tile"
self.python_api = paddle.tile
self.inputs = {
'X': np.random.randint(
10, size=(4, 4, 5)).astype("int32")
......@@ -169,26 +172,28 @@ class TestTileOpInteger(OpTest):
self.outputs = {'Out': output}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
# Situation 5: input x is Bool
class TestTileOpBoolean(OpTest):
def setUp(self):
self.op_type = "tile"
self.python_api = paddle.tile
self.inputs = {'X': np.random.randint(2, size=(2, 4, 5)).astype("bool")}
self.attrs = {'repeat_times': [2, 1, 4]}
output = np.tile(self.inputs['X'], (2, 1, 4))
self.outputs = {'Out': output}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
# Situation 56: input x is Integer
class TestTileOpInt64_t(OpTest):
def setUp(self):
self.op_type = "tile"
self.python_api = paddle.tile
self.inputs = {
'X': np.random.randint(
10, size=(2, 4, 5)).astype("int64")
......@@ -198,7 +203,7 @@ class TestTileOpInt64_t(OpTest):
self.outputs = {'Out': output}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
class TestTileError(unittest.TestCase):
......@@ -248,4 +253,5 @@ class TestTileAPI(unittest.TestCase):
if __name__ == "__main__":
paddle.enable_static()
unittest.main()
python/paddle/fluid/tests/unittests/test_trace_op.py
浏览文件 @ 733d3109
......@@ -27,14 +27,15 @@ import paddle
class TestTraceOp(OpTest):
def setUp(self):
self.op_type = "trace"
self.python_api = paddle.trace
self.init_config()
self.outputs = {'Out': self.target}
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
def test_check_grad(self):
self.check_grad(['Input'], 'Out')
self.check_grad(['Input'], 'Out', check_eager=True)
def init_config(self):
self.case = np.random.randn(20, 6).astype('float64')
......
python/paddle/fluid/tests/unittests/test_unfold_op.py
浏览文件 @ 733d3109
......@@ -95,6 +95,7 @@ class TestUnfoldOp(OpTest):
def setUp(self):
self.op_type = 'unfold'
self.set_data()
self.python_api = paddle.nn.functional.unfold
def test_check_output(self):
self.check_output(check_eager=True)
......
python/paddle/fluid/tests/unittests/test_where_index.py
浏览文件 @ 733d3109
......@@ -21,15 +21,17 @@ import paddle.fluid.core as core
from paddle.fluid.op import Operator
import paddle.fluid as fluid
from paddle.fluid import Program, program_guard
import paddle
class TestWhereIndexOp(OpTest):
def setUp(self):
self.op_type = "where_index"
self.pythona_api = paddle.fluid.layers.where
self.init_config()
def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)
def init_config(self):
self.inputs = {'Condition': np.array([True, False, True]), }
......@@ -111,4 +113,5 @@ class TestWhereRaiseError(unittest.TestCase):
if __name__ == "__main__":
paddle.enable_static()
unittest.main()
python/paddle/incubate/tensor/math.py
浏览文件 @ 733d3109
......@@ -15,6 +15,7 @@
from paddle.fluid.layer_helper import LayerHelper, in_dygraph_mode
from paddle.fluid.data_feeder import check_variable_and_dtype
from paddle import _C_ops
from paddle.fluid.framework import _in_eager_mode
__all__ = []
......@@ -51,6 +52,8 @@ def segment_sum(data, segment_ids, name=None):
"""
if in_dygraph_mode():
if _in_eager_mode():
return _C_ops.final_state_segment_pool(data, segment_idsm, "SUM")[0]
out, tmp = _C_ops.segment_pool(data, segment_ids, 'pooltype', "SUM")
return out
......@@ -104,6 +107,9 @@ def segment_mean(data, segment_ids, name=None):
"""
if in_dygraph_mode():
if _in_eager_mode():
return _C_ops.final_state_segment_pool(data, segment_idsm,
"MEAN")[0]
out, tmp = _C_ops.segment_pool(data, segment_ids, 'pooltype', "MEAN")
return out
......@@ -156,6 +162,8 @@ def segment_min(data, segment_ids, name=None):
"""
if in_dygraph_mode():
if _in_eager_mode():
return _C_ops.final_state_segment_pool(data, segment_idsm, "MIN")[0]
out, tmp = _C_ops.segment_pool(data, segment_ids, 'pooltype', "MIN")
return out
......@@ -208,6 +216,8 @@ def segment_max(data, segment_ids, name=None):
"""
if in_dygraph_mode():
if _in_eager_mode():
return _C_ops.final_state_segment_pool(data, segment_idsm, "MAX")[0]
out, tmp = _C_ops.segment_pool(data, segment_ids, 'pooltype', "MAX")
return out
......
python/paddle/metric/metrics.py
浏览文件 @ 733d3109
......@@ -22,7 +22,7 @@ import numpy as np
from ..fluid.data_feeder import check_variable_and_dtype
from ..fluid.layer_helper import LayerHelper
from ..fluid.framework import core, _varbase_creator, in_dygraph_mode
from ..fluid.framework import core, _varbase_creator, in_dygraph_mode, _in_eager_mode
import paddle
from paddle import _C_ops
......@@ -798,7 +798,7 @@ def accuracy(input, label, k=1, correct=None, total=None, name=None):
total = _varbase_creator(dtype="int32")
topk_out, topk_indices = paddle.topk(input, k=k)
if _in_eager_mode:
if _in_eager_mode():
_acc = _C_ops.final_state_accuracy(topk_out, topk_indices, label)
return _acc
_acc, _, _ = _C_ops.accuracy(topk_out, topk_indices, label, correct,
......
python/paddle/nn/functional/activation.py
浏览文件 @ 733d3109
......@@ -22,7 +22,7 @@ from ...tensor.math import multiply
import warnings
from ...fluid.layer_helper import LayerHelper
from ...fluid.framework import convert_np_dtype_to_dtype_
from ...fluid.framework import convert_np_dtype_to_dtype_, _in_eager_mode
from ...fluid.data_feeder import check_variable_and_dtype, check_dtype
import paddle
from paddle import _C_ops, in_dynamic_mode
......@@ -783,6 +783,8 @@ def selu(x,
"The alpha must be no less than zero. Received: {}.".format(alpha))
if in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_selu(x, scale, alpha)
return _C_ops.selu(x, 'scale', scale, 'alpha', alpha)
check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'selu')
......
python/paddle/tensor/linalg.py
浏览文件 @ 733d3109
......@@ -1439,6 +1439,8 @@ def bincount(x, weights=None, minlength=0, name=None):
raise TypeError("Elements in Input(x) should all be integers")
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_bincount(x, weights, minlength)
return _C_ops.bincount(x, weights, "minlength", minlength)
helper = LayerHelper('bincount', **locals())
......@@ -1748,6 +1750,8 @@ def matrix_power(x, n, name=None):
# [ 1.80555556 , -1.91666667 , 0.44444444 ]]
"""
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_matrix_power(x, n)
return _C_ops.matrix_power(x, "n", n)
check_variable_and_dtype(x, 'dtype', ['float32', 'float64'], 'matrix_power')
......@@ -2266,6 +2270,8 @@ def eigh(x, UPLO='L', name=None):
"""
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_eigh(x, UPLO)
return _C_ops.eigh(x, 'UPLO', UPLO)
def __check_input(x, UPLO):
......
python/paddle/tensor/logic.py
浏览文件 @ 733d3109
......@@ -453,8 +453,6 @@ def _bitwise_op(op_name, x, y, out=None, name=None, binary_op=True):
if binary_op:
return op(x, y)
else:
if _in_eager_mode():
return _C_op.final_state_bitewise_not(x)
return op(x)
check_variable_and_dtype(
......@@ -581,7 +579,8 @@ def bitwise_not(x, out=None, name=None):
res = paddle.bitwise_not(x)
print(res) # [4, 0, -2]
"""
if _in_eager_mode() and out == None:
return _C_op.final_state_bitwise_not(x)
return _bitwise_op(
op_name="bitwise_not", x=x, y=None, name=name, out=out, binary_op=False)
......
python/paddle/tensor/manipulation.py
浏览文件 @ 733d3109
......@@ -37,6 +37,7 @@ from ..fluid.dygraph.inplace_utils import inplace_apis_in_dygraph_only
import paddle
from paddle import _C_ops
from paddle.tensor.attribute import _complex_to_real_dtype, _real_to_complex_dtype
from paddle.fluid.framework import _in_eager_mode
__all__ = []
......@@ -947,6 +948,9 @@ def split(x, num_or_sections, axis=0, name=None):
print(out1.shape) # [3, 3, 5]
print(out2.shape) # [3, 3, 5]
"""
if paddle.in_dygraph_mode():
if _in_eager_mode():
return _C_ops.final_state_split(x, num_or_sections, dim)
return paddle.fluid.layers.split(
input=x, num_or_sections=num_or_sections, dim=axis, name=name)
......@@ -1746,6 +1750,8 @@ def tile(x, repeat_times, name=None):
# [[1, 2, 3], [1, 2, 3]]
"""
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_tile(x, repeat_times)
return _C_ops.tile(x, 'repeat_times', repeat_times)
check_type(repeat_times, 'repeat_times', (list, tuple, Variable), 'tile')
if isinstance(repeat_times, Variable):
......@@ -2822,6 +2828,8 @@ def take_along_axis(arr, indices, axis):
broadcast_shape_list[axis] = list(arr.shape)[axis]
broadcast_shape = tuple(broadcast_shape_list)
arr = paddle.broadcast_to(arr, broadcast_shape)
if _in_eager_mode():
return _C_ops.final_state_take_along_axis(arr, indices, axis)
return _C_ops.take_along_axis(arr, indices, 'Axis', axis)
check_variable_and_dtype(
arr, 'x', ['float16', 'float32', 'float64', 'int32', 'int64', 'uint8'],
......@@ -2887,6 +2895,9 @@ def put_along_axis(arr, indices, values, axis, reduce='assign'):
if broadcast_shape:
indices = paddle.broadcast_to(indices, broadcast_shape)
values = paddle.broadcast_to(values, indices.shape)
if _in_eager_mode():
return _C_ops.final_state_put_alone_axis(arr, indices, value, axis,
reduce)
return _C_ops.put_along_axis(arr, indices, values, "Axis", axis,
"Reduce", reduce)
......
python/paddle/tensor/math.py
浏览文件 @ 733d3109
......@@ -322,6 +322,8 @@ def subtract(x, y, name=None):
axis = -1
act = None
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_subtract( x, y)
return _elementwise_op_in_dygraph(
x, y, axis=axis, act=act, op_name=op_type)
return _elementwise_op(LayerHelper(op_type, **locals()))
......@@ -2344,6 +2346,8 @@ def trace(x, offset=0, axis1=0, axis2=1, name=None):
__check_input(input, offset, axis1, axis2)
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_trace( x, offset, axis1, axis2 )
return _C_ops.trace(x, 'offset', offset, 'axis1', axis1, 'axis2', axis2)
inputs = {'Input': [x]}
......@@ -2566,6 +2570,8 @@ def cumsum(x, axis=None, dtype=None, name=None):
x = cast(x, dtype)
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops._final_state_cumsum(x, axis, flatten, False, False)
if axis is None:
return _C_ops.cumsum(x, 'flatten', flatten)
else:
......@@ -2816,6 +2822,8 @@ def sign(x, name=None):
print(out) # [1.0, 0.0, -1.0, 1.0]
"""
if paddle.in_dynamic_mode():
if _in_eager_model():
return _C_op.final_state_sign(x)
return _C_ops.sign(x)
check_variable_and_dtype(x, 'x', ['float16', 'float32', 'float64'], 'sign')
......@@ -2897,6 +2905,8 @@ def increment(x, value=1.0, name=None):
"""
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_increment( x, value)
return _C_ops.increment(x, 'step', value)
check_variable_and_dtype(x, 'x', ['float32', 'float64', 'int32', 'int64'],
......@@ -3430,6 +3440,8 @@ def erfinv(x, name=None):
check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'erfinv')
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_erfinv( x )
return _C_ops.erfinv(x)
helper = LayerHelper('erfinv', **locals())
......
python/paddle/tensor/random.py
浏览文件 @ 733d3109
......@@ -22,6 +22,7 @@ from ..fluid.layers import utils
import paddle
from paddle import _C_ops
from paddle.static import Variable
from paddle.fluid.framework import _in_eager_mode
__all__ = []
......@@ -67,6 +68,8 @@ def bernoulli(x, name=None):
"""
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_bernoulli(x)
return _C_ops.bernoulli(x)
check_variable_and_dtype(x, "x", ["float32", "float64"], "bernoulli")
......@@ -175,6 +178,8 @@ def multinomial(x, num_samples=1, replacement=False, name=None):
"multinomial op is not supported on ROCM yet.")
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_multinomial(x, num_samples, replacement)
return _C_ops.multinomial(x, 'num_samples', num_samples, 'replacement',
replacement)
......
python/paddle/tensor/search.py
浏览文件 @ 733d3109
......@@ -23,6 +23,7 @@ from paddle.common_ops_import import Variable
from paddle.common_ops_import import VarDesc
from paddle import _C_ops
from .logic import logical_not
from paddle.fluid.framework import _in_eager_mode
# TODO: define searching & indexing functions of a tensor
# from ..fluid.layers import has_inf #DEFINE_ALIAS
......@@ -170,6 +171,9 @@ def argmax(x, axis=None, keepdim=False, dtype="int64", name=None):
axis = 0
if paddle.in_dynamic_mode():
if _in_eager_mode():
return _C_ops.final_state_argmin(x, axis, keepdim, flatten,
var_dtype)
out = _C_ops.arg_max(x, 'axis', axis, 'dtype', var_dtype, 'keepdims',
keepdim, 'flatten', flatten)
return out
......
python/paddle/utils/code_gen/api.yaml
浏览文件 @ 733d3109
......@@ -267,18 +267,6 @@
func : diagonal
backward : diagonal_grad
# softmax
- api : softmax
args : (Tensor x, int axis)
output : Tensor
infer_meta :
func : SoftmaxInferMeta
kernel :
func : softmax
backward : softmax_grad
# # maxout
# - api : maxout
# args : (Tensor x, int groups, int axis)
......@@ -298,6 +286,7 @@
param : [index]
kernel :
func : put_along_axis
dtype : x
backward : put_along_axis_grad
......@@ -310,6 +299,7 @@
param : [index]
kernel :
func : take_along_axis
dtype : x
backward : take_along_axis_grad
# matrix_power
......@@ -343,6 +333,7 @@
func : segment_pool
backward : segment_pool_grad
# accuracy
- api : accuracy
args : (Tensor x, Tensor indices, Tensor label)
......@@ -351,6 +342,7 @@
func : AccuracyInferMeta
kernel :
func : accuracy
dtype : x
# sin
- api : sin
......@@ -465,19 +457,9 @@
func : atanh
backward : atanh_grad
# relu
- api : relu
args : (Tensor x)
output : Tensor
infer_meta :
func : UnchangedInferMeta
kernel :
func : relu
backward : relu_grad
# arg_min # int64 ???? dtype
- api : arg_min
- api : argmin
args : (Tensor x, int64 axis, bool keepdims, bool flatten, int dtype)
output : Tensor
infer_meta :
......@@ -486,7 +468,7 @@
func : arg_min
# arg_max # int64 ???? dtype
- api : arg_max
- api : argmax
args : (Tensor x, int64 axis, bool keepdims, bool flatten, int dtype)
output : Tensor
infer_meta :
......
python/paddle/utils/code_gen/backward.yaml
浏览文件 @ 733d3109
......@@ -57,7 +57,7 @@
# - backward_api : norm_grad
# forward : norm (Tensor x, int axis, float epsilon, bool is_test) -> Tensor(out), Tensor(norm)
# args : (Tensor out_grad, Tensor x, Tensor norm, int axis, float epsilon, bool is_test)
# args : (Tensor x, Tensor norm, Tensor out_grad, int axis, float epsilon, bool is_test)
# output : Tensor(x_grad)
# infer_meta :
# func : UnchangedInferMeta
......
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