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提交 b07c563a 编写于 作者: G gongweibao
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Showing with 8 addition and 266 deletion
paddle/fluid/API.spec
浏览文件 @ b07c563a
......@@ -170,6 +170,13 @@ paddle.fluid.layers.unstack ArgSpec(args=['x', 'axis', 'num'], varargs=None, key
paddle.fluid.layers.sequence_enumerate ArgSpec(args=['input', 'win_size', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0, None))
paddle.fluid.layers.expand ArgSpec(args=['x', 'expand_times', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.sequence_concat ArgSpec(args=['input', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.uniform_random_batch_size_like ArgSpec(args=['input', 'shape', 'dtype', 'input_dim_idx', 'output_dim_idx', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=('float32', 0, 0, -1.0, 1.0, 0))
paddle.fluid.layers.gaussian_random ArgSpec(args=['shape', 'mean', 'std', 'seed', 'dtype', 'use_mkldnn'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32', False))
paddle.fluid.layers.sampling_id ArgSpec(args=['x', 'min', 'max', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32'))
paddle.fluid.layers.gaussian_random_batch_size_like ArgSpec(args=['input', 'shape', 'input_dim_idx', 'output_dim_idx', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0, 0, 0.0, 1.0, 0, 'float32'))
paddle.fluid.layers.sum ArgSpec(args=['x', 'use_mkldnn'], varargs=None, keywords=None, defaults=(False,))
paddle.fluid.layers.slice ArgSpec(args=['input', 'axes', 'starts', 'ends'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.shape ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.data ArgSpec(args=['name', 'shape', 'append_batch_size', 'dtype', 'lod_level', 'type', 'stop_gradient'], varargs=None, keywords=None, defaults=(True, 'float32', 0, VarType.LOD_TENSOR, True))
paddle.fluid.layers.open_files ArgSpec(args=['filenames', 'shapes', 'lod_levels', 'dtypes', 'thread_num', 'buffer_size', 'pass_num', 'is_test'], varargs=None, keywords=None, defaults=(None, None, 1, None))
paddle.fluid.layers.read_file ArgSpec(args=['reader'], varargs=None, keywords=None, defaults=None)
......@@ -249,13 +256,6 @@ paddle.fluid.layers.logical_and ArgSpec(args=[], varargs='args', keywords='kwarg
paddle.fluid.layers.logical_or ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logical_xor ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logical_not ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.uniform_random_batch_size_like ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.gaussian_random ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sampling_id ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.gaussian_random_batch_size_like ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sum ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.slice ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.shape ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.maxout ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sigmoid ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logsigmoid ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
......@@ -379,7 +379,7 @@ paddle.fluid.LoDTensor.__init__ 1. __init__(self: paddle.fluid.core.LoDTensor, a
paddle.fluid.LoDTensor.has_valid_recursive_sequence_lengths has_valid_recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor) -> bool
paddle.fluid.LoDTensor.lod lod(self: paddle.fluid.core.LoDTensor) -> List[List[int]]
paddle.fluid.LoDTensor.recursive_sequence_lengths recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor) -> List[List[int]]
paddle.fluid.LoDTensor.set 1. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CPUPlace) -> None 2. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CPUPlace) -> None 3. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CPUPlace) -> None 4. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CPUPlace) -> None 5. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CPUPlace) -> None 6. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CPUPlace) -> None 7. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CPUPlace) -> None 8. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int8], arg1: paddle::platform::CPUPlace) -> None 9. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CUDAPlace) -> None 10. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CUDAPlace) -> None 11. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CUDAPlace) -> None 12. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CUDAPlace) -> None 13. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CUDAPlace) -> None 14. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CUDAPlace) -> None 15. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CUDAPlace) -> None 16. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int8], arg1: paddle::platform::CUDAPlace) -> None 17. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CUDAPinnedPlace) -> None 18. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CUDAPinnedPlace) -> None 19. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CUDAPinnedPlace) -> None 20. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CUDAPinnedPlace) -> None 21. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CUDAPinnedPlace) -> None 22. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CUDAPinnedPlace) -> None 23. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CUDAPinnedPlace) -> None 24. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int8], arg1: paddle::platform::CUDAPinnedPlace) -> None
paddle.fluid.LoDTensor.set 1. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CPUPlace) -> None 2. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CPUPlace) -> None 3. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CPUPlace) -> None 4. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CPUPlace) -> None 5. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CPUPlace) -> None 6. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CPUPlace) -> None 7. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CPUPlace) -> None 8. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int8], arg1: paddle::platform::CPUPlace) -> None
paddle.fluid.LoDTensor.set_lod set_lod(self: paddle.fluid.core.LoDTensor, arg0: List[List[int]]) -> None
paddle.fluid.LoDTensor.set_recursive_sequence_lengths set_recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor, arg0: List[List[int]]) -> None
paddle.fluid.LoDTensor.shape shape(self: paddle.fluid.core.Tensor) -> List[int]
......
python/paddle/fluid/tests/unittests/op_test.py
浏览文件 @ b07c563a
......@@ -252,9 +252,6 @@ class OpTest(unittest.TestCase):
block = program.global_block()
self._append_ops(block)
from paddle.fluid.transpiler.details import program_to_code
program_to_code(program)
inputs = self._get_inputs(block)
outputs = self._get_outputs(block)
feed_map = self.feed_var(inputs, place)
......
tools/test_generator.py 已删除 100644 → 0
浏览文件 @ dda9c355
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import print_function
import re
import functools
import warnings
import string
from six.moves import cStringIO
from paddle.fluid.proto import framework_pb2
from paddle.fluid.framework import OpProtoHolder, Variable
from paddle.fluid.layer_helper import LayerHelper
g_filer_attrs = ['op_role', 'op_role_var', 'op_namescope']
def _convert_(name):
"""
Formatting.
Args:
name: The name/alias
This function takes in a name and converts it to a standard format of
group1_group2. Where as per the regular expression, group1 can have
alphabets and numbers and group2 has capital alphabets.
"""
s1 = re.sub('(.)([A-Z][a-z]+)', r'\1_\2', name)
return re.sub('([a-z0-9])([A-Z])', r'\1_\2', s1).lower()
def _get_inputs(op_type):
op_proto = OpProtoHolder.instance().get_op_proto(op_type)
inputs = dict()
for ipt in op_proto.inputs:
inputs[ipt.name] = ipt.comment
return inputs
def _get_outputs(op_type):
op_proto = OpProtoHolder.instance().get_op_proto(op_type)
outputs = {}
for ipt in op_proto.outputs:
outputs[ipt.name] = ""
return outputs
_two_dollar_pattern_ = re.compile(r"\$\$([^\$]+)\$\$")
_single_dollar_pattern_ = re.compile(r"\$([^\$]+)\$")
_two_bang_pattern_ = re.compile(r"!!([^!]+)!!")
def escape_math(text):
return _two_bang_pattern_.sub(
r'$$\1$$',
_single_dollar_pattern_.sub(r':math:`\1`',
_two_dollar_pattern_.sub(r"!!\1!!", text)))
def get_comment(op_type):
op_proto = OpProtoHolder.instance().get_op_proto(op_type)
comment_lines = op_proto.comment.split("\n")
comment = ""
for line in comment_lines:
line = line.strip()
if len(line) != 0:
comment += escape_math(line)
comment += " "
elif len(comment) != 0:
comment += "\n "
return comment
def _get_attrs(op_type):
op_proto = OpProtoHolder.instance().get_op_proto(op_type)
return op_proto.attrs
def get_indent_space(indent, space_num=4):
ret = ""
for i in range(0, indent * space_num):
ret += " "
return ret
def get_input_comments(op_type, indent=2):
ret = ""
inputs = _get_inputs(op_type)
for t in inputs:
ret += get_indent_space(2) + "%s (Type): %s\n" % (_convert_(t),
inputs[t])
for t in _get_attrs(op_type):
if t.name in g_filer_attrs:
continue
ret += get_indent_space(2) + "%s (%s): %s\n" % (
_convert_(t.name), t.type, _convert_(t.comment))
return ret
def get_output_comments(op_type, indent=2):
ret = ""
for t in _get_outputs(op_type):
ret += get_indent_space(2) + "output(${%s_type}): ${%s_comment}\n" % (
_convert_(t), _convert_(t))
return ret
def get_func_args(op_type):
ret = ""
inputs = _get_inputs(op_type)
for t in inputs:
ret += "%s," % _convert_(t)
for t in _get_attrs(op_type):
if t.name in g_filer_attrs:
continue
default = re.findall("\(.+\, default (.+)\(?\)", t.comment)
if len(default) > 0:
#print(default[0])
ret += "{}={},".format(_convert_(t.name), default[0])
continue
ret += "%s=," % _convert_(t.name)
return ret.strip(',')
def get_inputs(op_type):
ret = "inputs={"
inputs = _get_inputs(op_type)
for t in inputs:
ret += "'{}': {},".format(t, _convert_(t))
ret = ret.strip(",")
ret += "}"
if ret == "inputs={}":
return ""
return ret
def get_outputs(op_type):
ret = "outputs={"
inputs = _get_outputs(op_type)
for t in inputs:
ret += "'{}': {},".format(t, _convert_(t))
ret = ret.strip(",")
ret += "}"
if ret == "inputs={}":
return ""
return ret
def get_attrs(op_type):
ret = "attrs={"
for t in _get_attrs(op_type):
if t.name in g_filer_attrs:
continue
ret += "'%s': %s," % (t.name, _convert_(t.name))
ret = ret.strip(",")
ret += "}"
return ret
def get_outvars(op_type, indent=1):
inputs = _get_inputs(op_type)
if len(inputs) == 0:
return ""
ret = ""
for t in _get_outputs(op_type):
ret += get_indent_space(
indent
) + "%s = helper.create_tmp_variable(dtype=helper.input_dtype('%s'))\n" % (
(_convert_(t), list(inputs)[0]))
ret = ret.strip('\n')
return ret
def get_op_py(op_type):
input_comments = get_input_comments(op_type)
output_comments = get_output_comments(op_type)
args = get_func_args(op_type)
inputs = get_inputs(op_type)
outputs = get_outputs(op_type)
attrs = get_attrs(op_type)
out_vars = get_outvars(op_type)
comment = get_comment(op_type)
code = """
def {op_type}({args}):
\"\"\"
{comment}
Args:
{input_comments}
Returns:
{output_comments}
\"\"\"
helper = LayerHelper('{op_type}', **locals())
{generated_outvar}
helper.append_op(
type='{op_type}',
{inputs},
{outputs},
{attrs})
return out
""".format(
comment=comment,
input_comments=input_comments.strip('\n'),
output_comments=output_comments,
args=args,
generated_outvar=out_vars,
op_type=op_type,
inputs=inputs,
outputs=outputs,
attrs=attrs)
return code
#print(get_op_py("uniform_random_batch_size_like"))
#print(get_op_py("gaussian_random"))
print(get_op_py("sampling_id"))
print(get_op_py("gaussian_random_batch_size_like"))
print(get_op_py("sum"))
print(get_op_py("slice"))
print(get_op_py("shape"))
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