diff --git a/paddle/fluid/pybind/imperative.cc b/paddle/fluid/pybind/imperative.cc index 489dd198876204486fc94518fbef0c806d0543d4..da9900e2b271d08394cbc5e397f31b84e3b4d156 100644 --- a/paddle/fluid/pybind/imperative.cc +++ b/paddle/fluid/pybind/imperative.cc @@ -649,61 +649,47 @@ void BindImperative(py::module *m_ptr) { return self.NewVarBase(tensor.place(), false); }, py::return_value_policy::copy, R"DOC( - **Notes**: - **This API is ONLY available in Dygraph mode** - Returns a new Variable, detached from the current graph. - - Returns: - ( :ref:`api_guide_Variable_en` | dtype is same as current Variable): The detached Variable. + Returns a new Tensor, detached from the current graph. + Returns: The detached Tensor. Examples: .. code-block:: python - import paddle.fluid as fluid - from paddle.fluid.dygraph.base import to_variable - from paddle.fluid.dygraph import Linear - import numpy as np - - data = np.random.uniform(-1, 1, [30, 10, 32]).astype('float32') - with fluid.dygraph.guard(): - linear = Linear(32, 64) - data = to_variable(data) - x = linear(data) - y = x.detach() + import paddle + paddle.disable_static() + linear = Linear(32, 64) + data = paddle.uniform(shape=[30, 10, 32], -1, 1) + x = linear(data) + y = x.detach() )DOC") .def("clear_gradient", &imperative::VarBase::ClearGradient, R"DOC( - **Notes**: - **1. This API is ONLY available in Dygraph mode** - - **2. Use it only Variable has gradient, normally we use this for Parameters since other temporal Variable will be deleted by Python's GC** + Only for Tensor that has gradient, normally we use this for Parameters since other temporary Tensor doesen't has gradient. - Clear (set to ``0`` ) the Gradient of Current Variable + The Gradient of current Tensor will be set to ``0`` . Returns: None Examples: .. code-block:: python - import paddle.fluid as fluid - import numpy as np - - x = np.ones([2, 2], np.float32) - with fluid.dygraph.guard(): - inputs2 = [] - for _ in range(10): - tmp = fluid.dygraph.base.to_variable(x) - tmp.stop_gradient=False - inputs2.append(tmp) - ret2 = fluid.layers.sums(inputs2) - loss2 = fluid.layers.reduce_sum(ret2) - loss2.backward() - print(loss2.gradient()) - loss2.clear_gradient() - print("After clear {}".format(loss2.gradient())) + import paddle + paddle.disable_static() + + inputs = [] + for _ in range(10): + tmp = paddle.ones([2, 2]) + tmp.stop_gradient=False + inputs.append(tmp) + ret = paddle.sums(inputs2) + loss = paddle.reduce_sum(ret) + loss.backward() + print("Before clear_gradient {}".format(loss.grad)) + loss.clear_gradient() + print("After clear_gradient {}".format(loss.grad)) )DOC") .def("_run_backward", [](imperative::VarBase &self, const imperative::Tracer &tracer, diff --git a/python/paddle/fluid/dygraph/math_op_patch.py b/python/paddle/fluid/dygraph/math_op_patch.py index 3aa7b9dfc262810686319819f717f3cfd06b5e50..68206f62860852b1124b65da0e4124f60a2a8051 100644 --- a/python/paddle/fluid/dygraph/math_op_patch.py +++ b/python/paddle/fluid/dygraph/math_op_patch.py @@ -17,8 +17,7 @@ from __future__ import print_function from .. import core from ..framework import Variable, convert_np_dtype_to_dtype_, _varbase_creator from ..layers.layer_function_generator import OpProtoHolder -from ..layers import common_methods -from . import to_variable, no_grad +from . import no_grad import numpy as np import six @@ -53,47 +52,25 @@ def monkey_patch_math_varbase(): def astype(self, dtype): """ - **Notes**: - **The variable must be a** :ref:`api_fluid_Tensor` - Cast a variable to a specified data type. + Cast a Tensor to a specified data type. Args: - - self(Variable): The source variable - - dtype: The target data type + dtype: The target data type. Returns: - Variable: Variable with new dtype + Tensor: a new Tensor with target dtype Examples: - In Static Graph Mode: - - .. code-block:: python - - import paddle.fluid as fluid - - startup_prog = fluid.Program() - main_prog = fluid.Program() - with fluid.program_guard(startup_prog, main_prog): - original_variable = fluid.data(name = "new_variable", shape=[2,2], dtype='float32') - new_variable = original_variable.astype('int64') - print("new var's dtype is: {}".format(new_variable.dtype)) - - In Dygraph Mode: - .. code-block:: python - import paddle.fluid as fluid + import paddle import numpy as np - x = np.ones([2, 2], np.float32) - with fluid.dygraph.guard(): - original_variable = fluid.dygraph.to_variable(x) - print("original var's dtype is: {}, numpy dtype is {}".format(original_variable.dtype, original_variable.numpy().dtype)) - new_variable = original_variable.astype('int64') - print("new var's dtype is: {}, numpy dtype is {}".format(new_variable.dtype, new_variable.numpy().dtype)) + original_tensor = paddle.ones([2, 2]) + print("original tensor's dtype is: {}".format(original_tensor.dtype)) + new_tensor = original_tensor.astype('float32') + print("new tensor's dtype is: {}".format(new_tensor.dtype)) """ if not isinstance(dtype, core.VarDesc.VarType): @@ -147,6 +124,10 @@ def monkey_patch_math_varbase(): def _ndim_(var): return len(var.shape) + @property + def _size_(var): + return np.prod(var.shape) + def _scalar_add_(var, value): return _scalar_elementwise_op_(var, 1.0, value) @@ -208,7 +189,6 @@ def monkey_patch_math_varbase(): __impl__.__doc__ = """ {0} Args: - self(Tensor): left hand Tensor other_var(Tensor|float|int): right hand Tensor Returns: @@ -217,23 +197,7 @@ def monkey_patch_math_varbase(): __impl__.__name__ = method_name return __impl__ - # Todo(zhouwei): implement dygraph template to adapt to any function, receive('op_type', 'arg_template') - # Such as _method_creator_('addmm', 'x, y, alpha=1.0, beta=1.0, name=None'). It can reduce call time. - def _method_creator_(op_type, arg_template=None): - def __impl__(self): - op = getattr(core.ops, op_type) - return op(self) - - __impl__.__doc__ = """ - - See paddle.{}""".format(op_type) - __impl__.__name__ = op_type - - return __impl__ - varbase_methods = [ - # Type1: From custom fun or lambda - ## b=-a ('__neg__', _neg_), ('__float__', _float_), ('__long__', _long_), @@ -244,8 +208,7 @@ def monkey_patch_math_varbase(): ('dim', lambda x: len(x.shape)), ('ndimension', lambda x: len(x.shape)), ('ndim', _ndim_), - ('size', lambda x: x.shape), - # Type2: From Template that create core.ops automatically. It's recommended. + ('size', _size_), ('__add__', _binary_creator_('__add__', 'elementwise_add', False, _scalar_add_)), ## a+b == b+a. Do not need to reverse explicitly @@ -283,31 +246,7 @@ def monkey_patch_math_varbase(): ('__le__', _binary_creator_('__le__', 'less_equal', False, None)), ('__gt__', _binary_creator_('__gt__', 'greater_than', False, None)), ('__ge__', _binary_creator_('__ge__', 'greater_equal', False, None)), - ('__array_ufunc__', None), - ('sigmoid', _method_creator_('sigmoid', 'name=None')), - ('log_sigmoid', _method_creator_('logsigmoid', 'name=None')), - ('exp', _method_creator_('exp', 'name=None')), - ('tanh', _method_creator_('tanh', 'name=None')), - ('atan', _method_creator_('atan', 'name=None')), - ('tanh_shrink', _method_creator_('tanh_shrink', 'name=None')), - ('sqrt', _method_creator_('sqrt', 'name=None')), - ('rsqrt', _method_creator_('rsqrt', 'name=None')), - ('abs', _method_creator_('abs', 'name=None')), - ('ceil', _method_creator_('ceil', 'name=None')), - ('floor', _method_creator_('floor', 'name=None')), - ('cos', _method_creator_('cos', 'name=None')), - ('acos', _method_creator_('acos', 'name=None')), - ('asin', _method_creator_('asin', 'name=None')), - ('sin', _method_creator_('sin', 'name=None')), - ('sinh', _method_creator_('sinh', 'name=None')), - ('cosh', _method_creator_('cosh', 'name=None')), - ('round', _method_creator_('round', 'name=None')), - ('reciprocal', _method_creator_('reciprocal', 'name=None')), - ('square', _method_creator_('square', 'name=None')), - ('softplus', _method_creator_('softplus', 'name=None')), - ('softsign', _method_creator_('softsign', 'name=None')), - # Type3: Form module 'paddle.tensor' defaultly. - # It's not a goodway, because it will increase call time. + ('__array_ufunc__', None) ] global _already_patch_varbase @@ -318,7 +257,15 @@ def monkey_patch_math_varbase(): setattr(core.VarBase, method_name, method_impl) else: import paddle.tensor - for method_name in common_methods: + # Tensor method from module paddle.tensor + tensor_methods = paddle.tensor.linalg.__all__ + \ + paddle.tensor.math.__all__ + \ + paddle.tensor.logic.__all__ + \ + paddle.tensor.manipulation.__all__ + \ + paddle.tensor.search.__all__ + \ + paddle.tensor.stat.__all__ + \ + paddle.tensor.attribute.__all__ + for method_name in tensor_methods: if hasattr(core.VarBase, method_name): continue method_impl = getattr(paddle.tensor, method_name, None) if method_impl: setattr(core.VarBase, method_name, method_impl) diff --git a/python/paddle/fluid/layers/math_op_patch.py b/python/paddle/fluid/layers/math_op_patch.py index 4595f0cf93916d71a3d0ec582af1917500d68f12..92b58a7e2ee4c76af7047a14f67e40d76be76dc0 100644 --- a/python/paddle/fluid/layers/math_op_patch.py +++ b/python/paddle/fluid/layers/math_op_patch.py @@ -54,29 +54,6 @@ EXPRESSION_MAP = { "__ge__": "A >= B" } -# method for Tensor from paddle.tensor -# edit it when paddle.tensor has new method about Tensor operation -common_methods = [ - 'exp', 'tanh', 'atan', 'sqrt', 'rsqrt', 'abs', 'ceil', 'floor', 'cos', - 'acos', 'asin', 'sin', 'sinh', 'cosh', 'round', 'reciprocal', 'square', - 'rank', 'matmul', 'dot', 'norm', 'transpose', 'dist', 't', 'cross', - 'cholesky', 'bmm', 'histogram', 'equal', 'greater_equal', 'greater_than', - 'is_empty', 'isfinite', 'less_equal', 'less_than', 'logical_and', - 'logical_not', 'logical_or', 'logical_xor', 'not_equal', 'reduce_all', - 'reduce_any', 'allclose', 'equal_all', 'cast', 'expand', 'expand_as', - 'tile', 'flatten', 'gather', 'gather_nd', 'reshape', 'reverse', 'scatter', - 'scatter_nd_add', 'scatter_nd', 'shard_index', 'slice', 'split', 'squeeze', - 'strided_slice', 'unique', 'unique_with_counts', 'unsqueeze', 'flip', - 'unbind', 'roll', 'cumsum', 'increment', 'log', 'pow', 'reciprocal', - 'round', 'rsqrt', 'scale', 'sign', 'stanh', 'sum', 'reduce_prod', 'max', - 'min', 'mm', 'div', 'multiply', 'add', 'logsumexp', 'log1p', 'erf', - 'addcmul', 'addmm', 'clamp', 'trace', 'kron', 'argmax', 'argmin', 'argsort', - 'has_inf', 'has_nan', 'topk', 'index_select', 'nonzero', 'sort', - 'index_sample', 'mean', 'std', 'var', 'elementwise_add', 'elementwise_div', - 'elementwise_floordiv', 'elementwise_mod', 'elementwise_pow', - 'elementwise_sub' -] - _already_patch_variable = False @@ -372,7 +349,14 @@ def monkey_patch_variable(): setattr(Variable, method_name, method_impl) else: import paddle.tensor - for method_name in common_methods: + variabel_methods = paddle.tensor.linalg.__all__ + \ + paddle.tensor.math.__all__ + \ + paddle.tensor.logic.__all__ + \ + paddle.tensor.manipulation.__all__ + \ + paddle.tensor.search.__all__ + \ + paddle.tensor.stat.__all__ + \ + paddle.tensor.attribute.__all__ + for method_name in variabel_methods: if hasattr(Variable, method_name): continue method_impl = getattr(paddle.tensor, method_name, None) if method_impl: setattr(Variable, method_name, method_impl) diff --git a/python/paddle/fluid/tests/unittests/rnn/test_rnn_cells.py b/python/paddle/fluid/tests/unittests/rnn/test_rnn_cells.py index 8d2677229a03f7bdac14a93e176747ba0a5f1d6b..ab1127afa58dd93aa92688eebdf82292990f59b1 100644 --- a/python/paddle/fluid/tests/unittests/rnn/test_rnn_cells.py +++ b/python/paddle/fluid/tests/unittests/rnn/test_rnn_cells.py @@ -47,7 +47,7 @@ class TestSimpleRNNCell(unittest.TestCase): prev_h = np.random.randn(4, 32) y1, h1 = rnn1(x, prev_h) - y2, h2 = rnn2(paddle.to_variable(x), paddle.to_variable(prev_h)) + y2, h2 = rnn2(paddle.to_tensor(x), paddle.to_tensor(prev_h)) np.testing.assert_allclose(h1, h2.numpy(), atol=1e-8, rtol=1e-5) def test_with_zero_state(self): @@ -57,7 +57,7 @@ class TestSimpleRNNCell(unittest.TestCase): x = np.random.randn(4, 16) y1, h1 = rnn1(x) - y2, h2 = rnn2(paddle.to_variable(x)) + y2, h2 = rnn2(paddle.to_tensor(x)) np.testing.assert_allclose(h1, h2.numpy(), atol=1e-8, rtol=1e-5) def runTest(self): @@ -90,7 +90,7 @@ class TestGRUCell(unittest.TestCase): prev_h = np.random.randn(4, 32) y1, h1 = rnn1(x, prev_h) - y2, h2 = rnn2(paddle.to_variable(x), paddle.to_variable(prev_h)) + y2, h2 = rnn2(paddle.to_tensor(x), paddle.to_tensor(prev_h)) np.testing.assert_allclose(h1, h2.numpy(), atol=1e-8, rtol=1e-5) def test_with_zero_state(self): @@ -100,7 +100,7 @@ class TestGRUCell(unittest.TestCase): x = np.random.randn(4, 16) y1, h1 = rnn1(x) - y2, h2 = rnn2(paddle.to_variable(x)) + y2, h2 = rnn2(paddle.to_tensor(x)) np.testing.assert_allclose(h1, h2.numpy(), atol=1e-8, rtol=1e-5) def runTest(self): @@ -134,8 +134,8 @@ class TestLSTMCell(unittest.TestCase): y1, (h1, c1) = rnn1(x, (prev_h, prev_c)) y2, (h2, c2) = rnn2( - paddle.to_variable(x), - (paddle.to_variable(prev_h), paddle.to_variable(prev_c))) + paddle.to_tensor(x), + (paddle.to_tensor(prev_h), paddle.to_tensor(prev_c))) np.testing.assert_allclose(h1, h2.numpy(), atol=1e-8, rtol=1e-5) np.testing.assert_allclose(c1, c2.numpy(), atol=1e-8, rtol=1e-5) @@ -146,7 +146,7 @@ class TestLSTMCell(unittest.TestCase): x = np.random.randn(4, 16) y1, (h1, c1) = rnn1(x) - y2, (h2, c2) = rnn2(paddle.to_variable(x)) + y2, (h2, c2) = rnn2(paddle.to_tensor(x)) np.testing.assert_allclose(h1, h2.numpy(), atol=1e-8, rtol=1e-5) np.testing.assert_allclose(c1, c2.numpy(), atol=1e-8, rtol=1e-5) diff --git a/python/paddle/fluid/tests/unittests/rnn/test_rnn_nets.py b/python/paddle/fluid/tests/unittests/rnn/test_rnn_nets.py index ef297b3bb62497073fd667238cae8a83daaa4967..7c03b51837ef6f7be8021dca55daf3b43f7d3053 100644 --- a/python/paddle/fluid/tests/unittests/rnn/test_rnn_nets.py +++ b/python/paddle/fluid/tests/unittests/rnn/test_rnn_nets.py @@ -53,7 +53,7 @@ class TestSimpleRNN(unittest.TestCase): prev_h = np.random.randn(2 * self.num_directions, 4, 32) y1, h1 = rnn1(x, prev_h) - y2, h2 = rnn2(paddle.to_variable(x), paddle.to_variable(prev_h)) + y2, h2 = rnn2(paddle.to_tensor(x), paddle.to_tensor(prev_h)) np.testing.assert_allclose(y1, y2.numpy(), atol=1e-8, rtol=1e-5) np.testing.assert_allclose(h1, h2.numpy(), atol=1e-8, rtol=1e-5) @@ -66,7 +66,7 @@ class TestSimpleRNN(unittest.TestCase): x = np.transpose(x, [1, 0, 2]) y1, h1 = rnn1(x) - y2, h2 = rnn2(paddle.to_variable(x)) + y2, h2 = rnn2(paddle.to_tensor(x)) np.testing.assert_allclose(y1, y2.numpy(), atol=1e-8, rtol=1e-5) np.testing.assert_allclose(h1, h2.numpy(), atol=1e-8, rtol=1e-5) @@ -81,11 +81,11 @@ class TestSimpleRNN(unittest.TestCase): y1, h1 = rnn1(x, sequence_length=sequence_length) - seq_len = paddle.to_variable(sequence_length) + seq_len = paddle.to_tensor(sequence_length) mask = sequence_mask(seq_len, dtype=paddle.get_default_dtype()) if self.time_major: mask = paddle.transpose(mask, [1, 0]) - y2, h2 = rnn2(paddle.to_variable(x), sequence_length=seq_len) + y2, h2 = rnn2(paddle.to_tensor(x), sequence_length=seq_len) y2 = paddle.multiply(y2, mask, axis=0) np.testing.assert_allclose(y1, y2.numpy(), atol=1e-8, rtol=1e-5) @@ -133,7 +133,7 @@ class TestGRU(unittest.TestCase): prev_h = np.random.randn(2 * self.num_directions, 4, 32) y1, h1 = rnn1(x, prev_h) - y2, h2 = rnn2(paddle.to_variable(x), paddle.to_variable(prev_h)) + y2, h2 = rnn2(paddle.to_tensor(x), paddle.to_tensor(prev_h)) np.testing.assert_allclose(y1, y2.numpy(), atol=1e-8, rtol=1e-5) np.testing.assert_allclose(h1, h2.numpy(), atol=1e-8, rtol=1e-5) @@ -146,7 +146,7 @@ class TestGRU(unittest.TestCase): x = np.transpose(x, [1, 0, 2]) y1, h1 = rnn1(x) - y2, h2 = rnn2(paddle.to_variable(x)) + y2, h2 = rnn2(paddle.to_tensor(x)) np.testing.assert_allclose(y1, y2.numpy(), atol=1e-8, rtol=1e-5) np.testing.assert_allclose(h1, h2.numpy(), atol=1e-8, rtol=1e-5) @@ -161,11 +161,11 @@ class TestGRU(unittest.TestCase): y1, h1 = rnn1(x, sequence_length=sequence_length) - seq_len = paddle.to_variable(sequence_length) + seq_len = paddle.to_tensor(sequence_length) mask = sequence_mask(seq_len, dtype=paddle.get_default_dtype()) if self.time_major: mask = paddle.transpose(mask, [1, 0]) - y2, h2 = rnn2(paddle.to_variable(x), sequence_length=seq_len) + y2, h2 = rnn2(paddle.to_tensor(x), sequence_length=seq_len) y2 = paddle.multiply(y2, mask, axis=0) np.testing.assert_allclose(y1, y2.numpy(), atol=1e-8, rtol=1e-5) @@ -209,8 +209,8 @@ class TestLSTM(unittest.TestCase): y1, (h1, c1) = rnn1(x, (prev_h, prev_c)) y2, (h2, c2) = rnn2( - paddle.to_variable(x), - (paddle.to_variable(prev_h), paddle.to_variable(prev_c))) + paddle.to_tensor(x), + (paddle.to_tensor(prev_h), paddle.to_tensor(prev_c))) np.testing.assert_allclose(y1, y2.numpy(), atol=1e-8, rtol=1e-5) np.testing.assert_allclose(h1, h2.numpy(), atol=1e-8, rtol=1e-5) np.testing.assert_allclose(c1, c2.numpy(), atol=1e-8, rtol=1e-5) @@ -224,7 +224,7 @@ class TestLSTM(unittest.TestCase): x = np.transpose(x, [1, 0, 2]) y1, (h1, c1) = rnn1(x) - y2, (h2, c2) = rnn2(paddle.to_variable(x)) + y2, (h2, c2) = rnn2(paddle.to_tensor(x)) np.testing.assert_allclose(y1, y2.numpy(), atol=1e-8, rtol=1e-5) np.testing.assert_allclose(h1, h2.numpy(), atol=1e-8, rtol=1e-5) np.testing.assert_allclose(c1, c2.numpy(), atol=1e-8, rtol=1e-5) @@ -240,11 +240,11 @@ class TestLSTM(unittest.TestCase): y1, (h1, c1) = rnn1(x, sequence_length=sequence_length) - seq_len = paddle.to_variable(sequence_length) + seq_len = paddle.to_tensor(sequence_length) mask = sequence_mask(seq_len, dtype=paddle.get_default_dtype()) if self.time_major: mask = paddle.transpose(mask, [1, 0]) - y2, (h2, c2) = rnn2(paddle.to_variable(x), sequence_length=seq_len) + y2, (h2, c2) = rnn2(paddle.to_tensor(x), sequence_length=seq_len) y2 = paddle.multiply(y2, mask, axis=0) np.testing.assert_allclose(y1, y2.numpy(), atol=1e-8, rtol=1e-5) diff --git a/python/paddle/fluid/tests/unittests/test_math_op_patch_var_base.py b/python/paddle/fluid/tests/unittests/test_math_op_patch_var_base.py index a70862f40197c513a0cd04753553264708ee2a1c..5df04ddfc3d26492323153b8b26658db4325b7ec 100644 --- a/python/paddle/fluid/tests/unittests/test_math_op_patch_var_base.py +++ b/python/paddle/fluid/tests/unittests/test_math_op_patch_var_base.py @@ -19,6 +19,7 @@ import paddle import paddle.fluid as fluid import numpy as np import six +import inspect class TestMathOpPatchesVarBase(unittest.TestCase): @@ -302,21 +303,13 @@ class TestMathOpPatchesVarBase(unittest.TestCase): self.assertEqual(x.dim(), 2) self.assertEqual(x.ndimension(), 2) self.assertEqual(x.ndim, 2) - self.assertEqual(x.size(), [2, 3]) - self.assertTrue( - np.array_equal(x.sigmoid().numpy(), fluid.layers.sigmoid(x).numpy( - ))) - self.assertTrue( - np.array_equal(x.log_sigmoid().numpy(), - fluid.layers.logsigmoid(x).numpy())) + self.assertEqual(x.size, 6) + self.assertEqual(x.numel(), 6) self.assertTrue(np.array_equal(x.exp().numpy(), paddle.exp(x).numpy())) self.assertTrue( np.array_equal(x.tanh().numpy(), paddle.tanh(x).numpy())) self.assertTrue( np.array_equal(x.atan().numpy(), paddle.atan(x).numpy())) - self.assertTrue( - np.array_equal(x.tanh_shrink().numpy(), - fluid.layers.tanh_shrink(x).numpy())) self.assertTrue(np.array_equal(x.abs().numpy(), paddle.abs(x).numpy())) m = x.abs() self.assertTrue( @@ -344,12 +337,6 @@ class TestMathOpPatchesVarBase(unittest.TestCase): ))) self.assertTrue( np.array_equal(x.square().numpy(), paddle.square(x).numpy())) - self.assertTrue( - np.array_equal(x.softplus().numpy(), - fluid.layers.softplus(x).numpy())) - self.assertTrue( - np.array_equal(x.softsign().numpy(), - fluid.layers.softsign(x).numpy())) self.assertTrue( np.array_equal(x.rank().numpy(), paddle.rank(x).numpy())) self.assertTrue( @@ -422,6 +409,8 @@ class TestMathOpPatchesVarBase(unittest.TestCase): self.assertTrue(np.array_equal(x.reciprocal(), paddle.reciprocal(x))) # 2. Binary operation + self.assertTrue( + np.array_equal(x.divide(y).numpy(), paddle.divide(x, y).numpy())) self.assertTrue( np.array_equal( x.matmul(y, True, False).numpy(), @@ -501,6 +490,73 @@ class TestMathOpPatchesVarBase(unittest.TestCase): self.assertTrue( np.array_equal( x.logical_and(y).numpy(), paddle.logical_and(x, y).numpy())) + a = paddle.to_tensor([[1, 2], [3, 4]]) + b = paddle.to_tensor([[4, 3], [2, 1]]) + self.assertTrue( + np.array_equal( + x.where(a, b).numpy(), paddle.where(x, a, b).numpy())) + + self.assertTrue(inspect.ismethod(a.dot)) + self.assertTrue(inspect.ismethod(a.elementwise_add)) + self.assertTrue(inspect.ismethod(a.elementwise_div)) + self.assertTrue(inspect.ismethod(a.elementwise_floordiv)) + self.assertTrue(inspect.ismethod(a.elementwise_mod)) + self.assertTrue(inspect.ismethod(a.elementwise_sub)) + self.assertTrue(inspect.ismethod(a.logsumexp)) + self.assertTrue(inspect.ismethod(a.multiplex)) + self.assertTrue(inspect.ismethod(a.prod)) + self.assertTrue(inspect.ismethod(a.reduce_max)) + self.assertTrue(inspect.ismethod(a.reduce_min)) + self.assertTrue(inspect.ismethod(a.reduce_prod)) + self.assertTrue(inspect.ismethod(a.reduce_sum)) + self.assertTrue(inspect.ismethod(a.scale)) + self.assertTrue(inspect.ismethod(a.stanh)) + self.assertTrue(inspect.ismethod(a.sums)) + self.assertTrue(inspect.ismethod(a.elementwise_sum)) + self.assertTrue(inspect.ismethod(a.max)) + self.assertTrue(inspect.ismethod(a.maximum)) + self.assertTrue(inspect.ismethod(a.min)) + self.assertTrue(inspect.ismethod(a.minimum)) + self.assertTrue(inspect.ismethod(a.floor_divide)) + self.assertTrue(inspect.ismethod(a.remainder)) + self.assertTrue(inspect.ismethod(a.floor_mod)) + self.assertTrue(inspect.ismethod(a.multiply)) + self.assertTrue(inspect.ismethod(a.logsumexp)) + self.assertTrue(inspect.ismethod(a.inverse)) + self.assertTrue(inspect.ismethod(a.log1p)) + self.assertTrue(inspect.ismethod(a.erf)) + self.assertTrue(inspect.ismethod(a.addcmul)) + self.assertTrue(inspect.ismethod(a.addmm)) + self.assertTrue(inspect.ismethod(a.clip)) + self.assertTrue(inspect.ismethod(a.trace)) + self.assertTrue(inspect.ismethod(a.kron)) + self.assertTrue(inspect.ismethod(a.isinf)) + self.assertTrue(inspect.ismethod(a.isnan)) + self.assertTrue(inspect.ismethod(a.concat)) + self.assertTrue(inspect.ismethod(a.broadcast_to)) + self.assertTrue(inspect.ismethod(a.scatter_nd_add)) + self.assertTrue(inspect.ismethod(a.scatter_nd)) + self.assertTrue(inspect.ismethod(a.shard_index)) + self.assertTrue(inspect.ismethod(a.chunk)) + self.assertTrue(inspect.ismethod(a.stack)) + self.assertTrue(inspect.ismethod(a.strided_slice)) + self.assertTrue(inspect.ismethod(a.unsqueeze)) + self.assertTrue(inspect.ismethod(a.unstack)) + self.assertTrue(inspect.ismethod(a.argmax)) + self.assertTrue(inspect.ismethod(a.argmin)) + self.assertTrue(inspect.ismethod(a.argsort)) + self.assertTrue(inspect.ismethod(a.has_inf)) + self.assertTrue(inspect.ismethod(a.has_nan)) + self.assertTrue(inspect.ismethod(a.masked_select)) + self.assertTrue(inspect.ismethod(a.topk)) + self.assertTrue(inspect.ismethod(a.index_select)) + self.assertTrue(inspect.ismethod(a.nonzero)) + self.assertTrue(inspect.ismethod(a.sort)) + self.assertTrue(inspect.ismethod(a.index_sample)) + self.assertTrue(inspect.ismethod(a.mean)) + self.assertTrue(inspect.ismethod(a.reduce_mean)) + self.assertTrue(inspect.ismethod(a.std)) + self.assertTrue(inspect.ismethod(a.numel)) if __name__ == '__main__': diff --git a/python/paddle/fluid/tests/unittests/test_minimum_op.py b/python/paddle/fluid/tests/unittests/test_minimum_op.py index 4c08b7386ca2c5da04c0a289872dacf68a2ea040..a0673c82c5b341e550485ebdcee4e4616693d641 100644 --- a/python/paddle/fluid/tests/unittests/test_minimum_op.py +++ b/python/paddle/fluid/tests/unittests/test_minimum_op.py @@ -61,8 +61,8 @@ class ApiMinimumTest(unittest.TestCase): def test_dynamic_api(self): paddle.disable_static() np_x = np.array([10, 10]).astype('float64') - x = paddle.to_variable(self.input_x) - y = paddle.to_variable(self.input_y) + x = paddle.to_tensor(self.input_x) + y = paddle.to_tensor(self.input_y) z = paddle.minimum(x, y) np_z = z.numpy() z_expected = np.array(np.minimum(self.input_x, self.input_y)) @@ -73,8 +73,8 @@ class ApiMinimumTest(unittest.TestCase): np_x = np.random.rand(5, 4, 3, 2).astype("float64") np_y = np.random.rand(4, 3).astype("float64") - x = paddle.to_variable(self.input_x) - y = paddle.to_variable(self.input_y) + x = paddle.to_tensor(self.input_x) + y = paddle.to_tensor(self.input_y) result_1 = paddle.minimum(x, y, axis=1) result_2 = paddle.minimum(x, y, axis=-2) self.assertEqual((result_1.numpy() == result_2.numpy()).all(), True) diff --git a/python/paddle/fluid/tests/unittests/test_mse_loss.py b/python/paddle/fluid/tests/unittests/test_mse_loss.py index 753d96c44114a552f4bdd299602d7f13f672efbf..e327307e955308e78f6e9640681c842060a34882 100644 --- a/python/paddle/fluid/tests/unittests/test_mse_loss.py +++ b/python/paddle/fluid/tests/unittests/test_mse_loss.py @@ -205,8 +205,7 @@ class TestNNFunctionalMseLoss(unittest.TestCase): paddle.disable_static() dy_ret = paddle.nn.functional.mse_loss( - paddle.to_variable(input_np), - paddle.to_variable(target_np), 'mean') + paddle.to_tensor(input_np), paddle.to_tensor(target_np), 'mean') dy_result = dy_ret.numpy() sub = input_np - target_np @@ -240,8 +239,7 @@ class TestNNFunctionalMseLoss(unittest.TestCase): paddle.disable_static() dy_ret = paddle.nn.functional.mse_loss( - paddle.to_variable(input_np), - paddle.to_variable(target_np), 'sum') + paddle.to_tensor(input_np), paddle.to_tensor(target_np), 'sum') dy_result = dy_ret.numpy() sub = input_np - target_np @@ -275,8 +273,7 @@ class TestNNFunctionalMseLoss(unittest.TestCase): paddle.disable_static() dy_ret = paddle.nn.functional.mse_loss( - paddle.to_variable(input_np), - paddle.to_variable(target_np), 'none') + paddle.to_tensor(input_np), paddle.to_tensor(target_np), 'none') dy_result = dy_ret.numpy() sub = input_np - target_np diff --git a/python/paddle/fluid/tests/unittests/test_nll_loss.py b/python/paddle/fluid/tests/unittests/test_nll_loss.py index e7154193beaf788a9d20f3c131b1df3420918266..c07bf949af39e38222b05394f65977c7027e2f13 100644 --- a/python/paddle/fluid/tests/unittests/test_nll_loss.py +++ b/python/paddle/fluid/tests/unittests/test_nll_loss.py @@ -909,8 +909,8 @@ class TestNLLLossInvalidArgs(unittest.TestCase): with fluid.dygraph.guard(): x_np = np.random.random(size=(5, )).astype(np.float64) label_np = np.random.randint(0, 10, size=(5, )).astype(np.int64) - x = paddle.to_variable(x_np) - label = paddle.to_variable(label_np) + x = paddle.to_tensor(x_np) + label = paddle.to_tensor(label_np) nll_loss = paddle.nn.loss.NLLLoss() res = nll_loss(x, label) @@ -933,8 +933,8 @@ class TestNLLLossInvalidArgs(unittest.TestCase): with fluid.dygraph.guard(): x_np = np.random.random(size=(5, 3)).astype(np.float64) label_np = np.random.randint(0, 3, size=(5, )).astype(np.int64) - x = paddle.to_variable(x_np) - label = paddle.to_variable(label_np) + x = paddle.to_tensor(x_np) + label = paddle.to_tensor(label_np) nll_loss = paddle.nn.loss.NLLLoss(reduction='') res = nll_loss(x, label) @@ -957,8 +957,8 @@ class TestNLLLossInvalidArgs(unittest.TestCase): with fluid.dygraph.guard(): x_np = np.random.random(size=(5, 3)).astype(np.float64) label_np = np.random.randint(0, 3, size=(5, )).astype(np.int64) - x = paddle.to_variable(x_np) - label = paddle.to_variable(label_np) + x = paddle.to_tensor(x_np) + label = paddle.to_tensor(label_np) res = paddle.nn.functional.nll_loss(x, label, reduction='') self.assertRaises( diff --git a/python/paddle/fluid/tests/unittests/test_nn_margin_rank_loss.py b/python/paddle/fluid/tests/unittests/test_nn_margin_rank_loss.py index 0ebe769fb9bce1aee8412ccebc216c2c85e97775..8ee3b2ac20320c3b82eb7bb81509a9a84ce959a7 100644 --- a/python/paddle/fluid/tests/unittests/test_nn_margin_rank_loss.py +++ b/python/paddle/fluid/tests/unittests/test_nn_margin_rank_loss.py @@ -101,9 +101,9 @@ def create_test_case(margin, reduction): def run_dynamic_functional_api(self, place): paddle.disable_static(place) - x = paddle.to_variable(self.x_data) - y = paddle.to_variable(self.y_data) - label = paddle.to_variable(self.label_data) + x = paddle.to_tensor(self.x_data) + y = paddle.to_tensor(self.y_data) + label = paddle.to_tensor(self.label_data) result = paddle.nn.functional.margin_ranking_loss(x, y, label, margin, reduction) @@ -117,9 +117,9 @@ def create_test_case(margin, reduction): def run_dynamic_api(self, place): paddle.disable_static(place) - x = paddle.to_variable(self.x_data) - y = paddle.to_variable(self.y_data) - label = paddle.to_variable(self.label_data) + x = paddle.to_tensor(self.x_data) + y = paddle.to_tensor(self.y_data) + label = paddle.to_tensor(self.label_data) margin_rank_loss = paddle.nn.loss.MarginRankingLoss( margin=margin, reduction=reduction) result = margin_rank_loss(x, y, label) @@ -134,9 +134,9 @@ def create_test_case(margin, reduction): def run_dynamic_broadcast_api(self, place): paddle.disable_static(place) label_data = np.random.choice([-1, 1], size=[10]).astype("float64") - x = paddle.to_variable(self.x_data) - y = paddle.to_variable(self.y_data) - label = paddle.to_variable(label_data) + x = paddle.to_tensor(self.x_data) + y = paddle.to_tensor(self.y_data) + label = paddle.to_tensor(label_data) margin_rank_loss = paddle.nn.loss.MarginRankingLoss( margin=margin, reduction=reduction) result = margin_rank_loss(x, y, label) diff --git a/python/paddle/fluid/tests/unittests/test_nn_sigmoid_op.py b/python/paddle/fluid/tests/unittests/test_nn_sigmoid_op.py index d52a1f5d5b16ca7e0d58230a1a17624e5bff0b02..90132a0923df716e9e2a0224671006cb62c1bba0 100644 --- a/python/paddle/fluid/tests/unittests/test_nn_sigmoid_op.py +++ b/python/paddle/fluid/tests/unittests/test_nn_sigmoid_op.py @@ -56,7 +56,7 @@ class TestNNSigmoidAPI(unittest.TestCase): def check_dynamic_api(self, place): paddle.disable_static(place) - x = paddle.to_variable(self.x) + x = paddle.to_tensor(self.x) mysigmoid = nn.Sigmoid() y = mysigmoid(x) self.assertTrue(np.allclose(y.numpy(), self.y)) @@ -94,7 +94,7 @@ class TestNNFunctionalSigmoidAPI(unittest.TestCase): def check_dynamic_api(self): paddle.disable_static() - x = paddle.to_variable(self.x) + x = paddle.to_tensor(self.x) y = functional.sigmoid(x) self.assertTrue(np.allclose(y.numpy(), self.y)) diff --git a/python/paddle/fluid/tests/unittests/test_numel_op.py b/python/paddle/fluid/tests/unittests/test_numel_op.py index 8512bc99e7451c73e5513b834fb6aa448717c646..800706e5965dffedadb61c384d946c8ed28bf826 100644 --- a/python/paddle/fluid/tests/unittests/test_numel_op.py +++ b/python/paddle/fluid/tests/unittests/test_numel_op.py @@ -76,8 +76,8 @@ class TestNumelOoAPI(unittest.TestCase): paddle.disable_static(paddle.CPUPlace()) input_1 = np.random.random([2, 1, 4, 5]).astype("int32") input_2 = np.random.random([1, 4, 5]).astype("int32") - x_1 = paddle.to_variable(input_1) - x_2 = paddle.to_variable(input_2) + x_1 = paddle.to_tensor(input_1) + x_2 = paddle.to_tensor(input_2) out_1 = paddle.numel(x_1) out_2 = paddle.numel(x_2) assert (np.array_equal(out_1.numpy().item(0), np.size(input_1))) diff --git a/python/paddle/fluid/tests/unittests/test_ones_like.py b/python/paddle/fluid/tests/unittests/test_ones_like.py index c1e6a3377710f98184e9541e287b911def89cd81..bb0d6f07bdbde18d155b66c7d014503747ebd887 100644 --- a/python/paddle/fluid/tests/unittests/test_ones_like.py +++ b/python/paddle/fluid/tests/unittests/test_ones_like.py @@ -63,7 +63,7 @@ class TestOnesLikeImpeartive(unittest.TestCase): place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda( ) else fluid.CPUPlace() paddle.disable_static(place) - x = paddle.to_variable(np.ones(shape)) + x = paddle.to_tensor(np.ones(shape)) for dtype in [np.bool, np.float32, np.float64, np.int32, np.int64]: out = ones_like(x, dtype) self.assertEqual((out.numpy() == np.ones(shape, dtype)).all(), True) diff --git a/python/paddle/fluid/tests/unittests/test_pairwise_distance.py b/python/paddle/fluid/tests/unittests/test_pairwise_distance.py index baf0efa6ec2e7edafb8d331423a7b47155283c21..cf138e67726163d3d1c990a180fa229b88fed99f 100644 --- a/python/paddle/fluid/tests/unittests/test_pairwise_distance.py +++ b/python/paddle/fluid/tests/unittests/test_pairwise_distance.py @@ -48,8 +48,8 @@ def test_static(x_np, y_np, p=2.0, epsilon=1e-6, keepdim=False): def test_dygraph(x_np, y_np, p=2.0, epsilon=1e-6, keepdim=False): paddle.disable_static() - x = paddle.to_variable(x_np) - y = paddle.to_variable(y_np) + x = paddle.to_tensor(x_np) + y = paddle.to_tensor(y_np) dist = paddle.nn.layer.distance.PairwiseDistance( p=p, epsilon=epsilon, keepdim=keepdim) distance = dist(x, y) diff --git a/python/paddle/fluid/tests/unittests/test_sort_op.py b/python/paddle/fluid/tests/unittests/test_sort_op.py index 015b72fd1c5275f758a109451110f61b97c4a0c7..366e0c7a3fa3ee714162e6041aa0d52dbfb30746 100644 --- a/python/paddle/fluid/tests/unittests/test_sort_op.py +++ b/python/paddle/fluid/tests/unittests/test_sort_op.py @@ -72,14 +72,14 @@ class TestSortDygraph(unittest.TestCase): def test_api_0(self): paddle.disable_static(self.place) - var_x = paddle.to_variable(self.input_data) + var_x = paddle.to_tensor(self.input_data) out = paddle.sort(var_x) self.assertEqual((np.sort(self.input_data) == out.numpy()).all(), True) paddle.enable_static() def test_api_1(self): paddle.disable_static(self.place) - var_x = paddle.to_variable(self.input_data) + var_x = paddle.to_tensor(self.input_data) out = paddle.sort(var_x, axis=-1) self.assertEqual( (np.sort( diff --git a/python/paddle/fluid/tests/unittests/test_tile_op.py b/python/paddle/fluid/tests/unittests/test_tile_op.py index 5aaf31993448ab0ff0c69f648cfa84c62d3e198b..b0f065a26a006ee3553a84938fb5b6b2db7b3172 100644 --- a/python/paddle/fluid/tests/unittests/test_tile_op.py +++ b/python/paddle/fluid/tests/unittests/test_tile_op.py @@ -230,13 +230,13 @@ class TestTileAPI(unittest.TestCase): def test_api(self): with fluid.dygraph.guard(): np_x = np.random.random([12, 14]).astype("float32") - x = paddle.to_variable(np_x) + x = paddle.to_tensor(np_x) positive_2 = np.array([2]).astype("int32") - positive_2 = paddle.to_variable(positive_2) + positive_2 = paddle.to_tensor(positive_2) repeat_times = np.array([2, 3]).astype("int32") - repeat_times = paddle.to_variable(repeat_times) + repeat_times = paddle.to_tensor(repeat_times) out_1 = paddle.tile(x, repeat_times=[2, 3]) out_2 = paddle.tile(x, repeat_times=[positive_2, 3]) diff --git a/python/paddle/fluid/tests/unittests/test_transformer_api.py b/python/paddle/fluid/tests/unittests/test_transformer_api.py index bd76edc9d8cadf14c6cf224b7708ff4acd6efef4..7c7a71a3be1b508c850048c3945f29ef7424654c 100644 --- a/python/paddle/fluid/tests/unittests/test_transformer_api.py +++ b/python/paddle/fluid/tests/unittests/test_transformer_api.py @@ -234,23 +234,23 @@ class TestTransformer(unittest.TestCase): if cache_dict: if 'k' and 'v' in cache_dict: cache_obj = multi_head_attn.Cache( - paddle.to_variable(cache_dict['k']), - paddle.to_variable(cache_dict['v'])) + paddle.to_tensor(cache_dict['k']), + paddle.to_tensor(cache_dict['v'])) elif 'static_k' and 'static_v' in cache_dict: cache_obj = multi_head_attn.StaticCache( - paddle.to_variable(cache_dict['static_k']), - paddle.to_variable(cache_dict['static_v'])) + paddle.to_tensor(cache_dict['static_k']), + paddle.to_tensor(cache_dict['static_v'])) if attn_mask is not None: attn_output = multi_head_attn( - paddle.to_variable(query), - paddle.to_variable(key), - paddle.to_variable(value), - paddle.to_variable(attn_mask), cache_obj) + paddle.to_tensor(query), + paddle.to_tensor(key), + paddle.to_tensor(value), + paddle.to_tensor(attn_mask), cache_obj) else: attn_output = multi_head_attn( - paddle.to_variable(query), - paddle.to_variable(key), - paddle.to_variable(value), attn_mask, cache_obj) + paddle.to_tensor(query), + paddle.to_tensor(key), + paddle.to_tensor(value), attn_mask, cache_obj) attn_output = attn_output[0] if cache_dict else attn_output # implementation by numpy @@ -296,16 +296,16 @@ class TestTransformer(unittest.TestCase): attn_dropout, act_dropout) encoder_output = encoder_layer( - paddle.to_variable(src), - paddle.to_variable(src_mask)) # paddle.to_variable(src_mask)) + paddle.to_tensor(src), + paddle.to_tensor(src_mask)) # paddle.to_tensor(src_mask)) # 4.numpy: # paddle self attention self_attn = MultiHeadAttention( d_model, n_head, dropout=attn_dropout) attn_output = self_attn( - paddle.to_variable(src), - paddle.to_variable(src), - paddle.to_variable(src), paddle.to_variable(src_mask)).numpy() + paddle.to_tensor(src), + paddle.to_tensor(src), + paddle.to_tensor(src), paddle.to_tensor(src_mask)).numpy() src = attn_output + residual src_norm = layer_norm(src, d_model, encoder_layer.norm1) @@ -348,13 +348,13 @@ class TestTransformer(unittest.TestCase): cache_objs = None if cache: cache_objs = decoder_layer.gen_cache( - paddle.to_variable(memory)) + paddle.to_tensor(memory)) decoder_output = decoder_layer( - paddle.to_variable(tgt), - paddle.to_variable(memory), - paddle.to_variable(tgt_mask), - paddle.to_variable(memory_mask), cache_objs) + paddle.to_tensor(tgt), + paddle.to_tensor(memory), + paddle.to_tensor(tgt_mask), + paddle.to_tensor(memory_mask), cache_objs) decoder_output = decoder_output[0].numpy( ) if cache else decoder_output.numpy() @@ -365,10 +365,10 @@ class TestTransformer(unittest.TestCase): self_attn_cache = cache_objs[ 0] if cache_objs is not None else None tgt = self_attn( - paddle.to_variable(tgt), - paddle.to_variable(tgt), - paddle.to_variable(tgt), - paddle.to_variable(tgt_mask), self_attn_cache) + paddle.to_tensor(tgt), + paddle.to_tensor(tgt), + paddle.to_tensor(tgt), + paddle.to_tensor(tgt_mask), self_attn_cache) tgt = tgt[0].numpy() if cache else tgt.numpy() @@ -380,10 +380,10 @@ class TestTransformer(unittest.TestCase): cross_attn_cache = cache_objs[ 1] if cache_objs is not None else None tgt = cross_attn( - paddle.to_variable(tgt_norm), - paddle.to_variable(memory), - paddle.to_variable(memory), - paddle.to_variable(memory_mask), cross_attn_cache) + paddle.to_tensor(tgt_norm), + paddle.to_tensor(memory), + paddle.to_tensor(memory), + paddle.to_tensor(memory_mask), cross_attn_cache) tgt = tgt[0].numpy() if cache else tgt.numpy() # postprocess @@ -416,7 +416,7 @@ class TestTransformer(unittest.TestCase): encoder = TransformerEncoder(encoder_layer, num_layers) # src, src_mask enc_output = encoder( - paddle.to_variable(src), paddle.to_variable(src_mask)) + paddle.to_tensor(src), paddle.to_tensor(src_mask)) def test_decoder(self): batch_size, d_model, n_head, dim_feedforward, dropout, _, _, source_length, target_length = generate_basic_params( @@ -438,9 +438,9 @@ class TestTransformer(unittest.TestCase): decoder = TransformerDecoder(decoder_layer, num_layers) output = decoder( - paddle.to_variable(tgt), - paddle.to_variable(memory), - paddle.to_variable(tgt_mask), paddle.to_variable(memory_mask)) + paddle.to_tensor(tgt), + paddle.to_tensor(memory), + paddle.to_tensor(tgt_mask), paddle.to_tensor(memory_mask)) def test_transformer(self): batch_size, d_model, n_head, dim_feedforward, dropout, _, _, source_length, target_length = generate_basic_params( @@ -453,24 +453,24 @@ class TestTransformer(unittest.TestCase): n_head, dim_feedforward=dim_feedforward, dropout=dropout) - src = paddle.to_variable( + src = paddle.to_tensor( np.random.rand(batch_size, source_length, d_model).astype( "float32")) - tgt = paddle.to_variable( + tgt = paddle.to_tensor( np.random.rand(batch_size, target_length, d_model).astype( "float32")) src_mask = np.zeros((batch_size, n_head, source_length, source_length)).astype("float32") src_mask[0][0][0][0] = -np.inf - src_mask = paddle.to_variable(src_mask) + src_mask = paddle.to_tensor(src_mask) tgt_mask = np.zeros((batch_size, n_head, target_length, target_length)).astype("float32") tgt_mask[0][0][0][0] = -1e9 memory_mask = np.zeros((batch_size, n_head, target_length, source_length)).astype("float32") memory_mask[0][0][0][0] = -1e9 - tgt_mask, memory_mask = paddle.to_variable( - tgt_mask), paddle.to_variable(memory_mask) + tgt_mask, memory_mask = paddle.to_tensor( + tgt_mask), paddle.to_tensor(memory_mask) trans_output = transformer(src, tgt, src_mask, tgt_mask, memory_mask) diff --git a/python/paddle/fluid/tests/unittests/test_warpctc_op.py b/python/paddle/fluid/tests/unittests/test_warpctc_op.py index 6bc42f0712a1a8c9f9a0640e06042c42e7cc948f..c4155e0d8260fe1fdc4a0e49e955fc2bbff0fc89 100644 --- a/python/paddle/fluid/tests/unittests/test_warpctc_op.py +++ b/python/paddle/fluid/tests/unittests/test_warpctc_op.py @@ -424,10 +424,10 @@ class TestCTCLossAPICase(unittest.TestCase): loss_np = ctc.forward() paddle.disable_static() - softmax = paddle.to_variable(logits) - labels = paddle.to_variable(labels) - logits_length = paddle.to_variable(self.logits_length) - labels_length = paddle.to_variable(self.labels_length) + softmax = paddle.to_tensor(logits) + labels = paddle.to_tensor(labels) + logits_length = paddle.to_tensor(self.logits_length) + labels_length = paddle.to_tensor(self.labels_length) loss_pd_mean = F.ctc_loss( softmax, labels, @@ -477,10 +477,10 @@ class TestCTCLossAPICase(unittest.TestCase): loss_np = ctc.forward() paddle.disable_static() - softmax = paddle.to_variable(logits) - labels = paddle.to_variable(labels) - logits_length = paddle.to_variable(self.logits_length) - labels_length = paddle.to_variable(self.labels_length) + softmax = paddle.to_tensor(logits) + labels = paddle.to_tensor(labels) + logits_length = paddle.to_tensor(self.logits_length) + labels_length = paddle.to_tensor(self.labels_length) loss_pd = paddle.nn.CTCLoss(self.blank, 'none')( softmax, labels, logits_length, labels_length) diff --git a/python/paddle/tensor/manipulation.py b/python/paddle/tensor/manipulation.py index 9de407841fb461713d00f997afdf33a38a531245..dc6a04a4723bd92dbe1c76fce5b3e52981136211 100644 --- a/python/paddle/tensor/manipulation.py +++ b/python/paddle/tensor/manipulation.py @@ -53,7 +53,7 @@ __all__ = [ 'shard_index', 'slice', 'split', - 'chunk' + 'chunk', 'squeeze', 'stack', 'strided_slice',