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test=develop, move simple rnn cell to test_imperative

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revert-15470-feature/imperative
JiabinYang 6 years ago
parent 05bbe4e153
commit 33590b583f
3 changed files with 113 additions and 95 deletions
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93
python/paddle/fluid/imperative/nn.py
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@ -23,7 +23,7 @@ from ..framework import Variable, OpProtoHolder
from ..param_attr import ParamAttr
from ..initializer import Normal, Constant
__all__ = ['Conv2D', 'Pool2D', 'FC', 'SimpleRNNCell']
__all__ = ['Conv2D', 'Pool2D', 'FC']
class Conv2D(layers.Layer):
@ -274,94 +274,3 @@ class FC(layers.Layer):
out = bias_out
# add activation
return self._helper.append_activation(out)
class SimpleRNNCell(layers.Layer):
def __init__(self, step_input_size, hidden_size, output_size, param_attr):
super(SimpleRNNCell, self).__init__()
self.step_input_size = step_input_size
self.hidden_size = hidden_size
self.output_size = output_size
self._dype = core.VarDesc.VarType.FP32
from ..layer_helper import LayerHelper
self._helper = LayerHelper(
'SimpleRNNCell', act="tanh", param_attr=param_attr)
def _build_once(self, inputs, pre_hidden):
i2h_param_shape = [self.step_input_size, self.hidden_size]
h2h_param_shape = [self.hidden_size, self.hidden_size]
h2o_param_shape = [self.output_size, self.hidden_size]
self._i2h_w = self._helper.create_parameter(
attr=self._helper.param_attr,
shape=i2h_param_shape,
dtype=self._dtype,
is_bias=False)
self._h2h_w = self._helper.create_parameter(
attr=self._helper.param_attr,
shape=h2h_param_shape,
dtype=self._dtype,
is_bias=False)
self._h2o_w = self._helper.create_parameter(
attr=self._helper.param_attr,
shape=h2o_param_shape,
dtype=self._dtype,
is_bias=False)
def forward(self, input, pre_hidden):
tmp_i2h = self._helper.create_variable_for_type_inference(self._dtype)
tmp_h2h = self._helper.create_variable_for_type_inference(self._dtype)
hidden = self._helper.create_variable_for_type_inference(self._dype)
out = self._helper.create_variable_for_type_inference(self._dype)
softmax_out = self._helper.create_variable_for_type_inference(
self._dtype)
reduce_out = self._helper.create_variable_for_type_inference(
self._dtype)
self._helper.append_op(
type="mul",
inputs={"X": input,
"Y": self._i2h_w},
outputs={"Out": tmp_i2h},
attrs={"x_num_col_dims": 1,
"y_num_col_dims": 1})
self._helper.append_op(
type="mul",
inputs={"X": pre_hidden,
"Y": self._h2h_w},
outputs={"Out": tmp_h2h},
attrs={"x_num_col_dims": 1,
"y_num_col_dims": 1})
self._helper.append_op(
type="elementwise_add",
inputs={'X': tmp_h2h,
'Y': tmp_i2h},
outputs={'Out': hidden},
attrs={'axis': -1,
'use_mkldnn': False})
hidden = self._helper.append_activation(hidden)
self._helper.append_op(
type="mul",
inputs={"X": hidden,
"Y": self._h2o_w},
outputs={"Out": out},
attrs={"x_num_col_dims": 1,
"y_num_col_dims": 1})
self._helper.append_op(
type="softmax",
inputs={"X": out},
outputs={"Out": softmax_out},
attrs={"use_cudnn": False})
self._helper.append_op(
type='reduce_sum',
inputs={'X': softmax_out},
outputs={'Out': reduce_out},
attrs={'dim': None,
'keep_dim': False,
'reduce_all': True})
return reduce_out, hidden

94
python/paddle/fluid/tests/unittests/test_imperative.py
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@ -20,9 +20,6 @@ import sys
import paddle.fluid as fluid
from paddle.fluid import core
from paddle.fluid.imperative.nn import FC
from paddle.fluid.imperative.nn import SimpleRNNCell
from typing import List, Any, Tuple
from test_imperative_base import new_program_scope
@ -69,6 +66,97 @@ class MLP(fluid.imperative.Layer):
return x
class SimpleRNNCell(fluid.imperative.Layer):
def __init__(self, step_input_size, hidden_size, output_size, param_attr):
super(SimpleRNNCell, self).__init__()
self.step_input_size = step_input_size
self.hidden_size = hidden_size
self.output_size = output_size
self._dype = core.VarDesc.VarType.FP32
from paddle.fluid.layer_helper import LayerHelper
self._helper = LayerHelper(
'SimpleRNNCell', act="tanh", param_attr=param_attr)
def _build_once(self, inputs, pre_hidden):
i2h_param_shape = [self.step_input_size, self.hidden_size]
h2h_param_shape = [self.hidden_size, self.hidden_size]
h2o_param_shape = [self.output_size, self.hidden_size]
self._i2h_w = self._helper.create_parameter(
attr=self._helper.param_attr,
shape=i2h_param_shape,
dtype=self._dtype,
is_bias=False)
self._h2h_w = self._helper.create_parameter(
attr=self._helper.param_attr,
shape=h2h_param_shape,
dtype=self._dtype,
is_bias=False)
self._h2o_w = self._helper.create_parameter(
attr=self._helper.param_attr,
shape=h2o_param_shape,
dtype=self._dtype,
is_bias=False)
def forward(self, input, pre_hidden):
tmp_i2h = self._helper.create_variable_for_type_inference(self._dtype)
tmp_h2h = self._helper.create_variable_for_type_inference(self._dtype)
hidden = self._helper.create_variable_for_type_inference(self._dype)
out = self._helper.create_variable_for_type_inference(self._dype)
softmax_out = self._helper.create_variable_for_type_inference(
self._dtype)
reduce_out = self._helper.create_variable_for_type_inference(
self._dtype)
self._helper.append_op(
type="mul",
inputs={"X": input,
"Y": self._i2h_w},
outputs={"Out": tmp_i2h},
attrs={"x_num_col_dims": 1,
"y_num_col_dims": 1})
self._helper.append_op(
type="mul",
inputs={"X": pre_hidden,
"Y": self._h2h_w},
outputs={"Out": tmp_h2h},
attrs={"x_num_col_dims": 1,
"y_num_col_dims": 1})
self._helper.append_op(
type="elementwise_add",
inputs={'X': tmp_h2h,
'Y': tmp_i2h},
outputs={'Out': hidden},
attrs={'axis': -1,
'use_mkldnn': False})
hidden = self._helper.append_activation(hidden)
self._helper.append_op(
type="mul",
inputs={"X": hidden,
"Y": self._h2o_w},
outputs={"Out": out},
attrs={"x_num_col_dims": 1,
"y_num_col_dims": 1})
self._helper.append_op(
type="softmax",
inputs={"X": out},
outputs={"Out": softmax_out},
attrs={"use_cudnn": False})
self._helper.append_op(
type='reduce_sum',
inputs={'X': softmax_out},
outputs={'Out': reduce_out},
attrs={'dim': None,
'keep_dim': False,
'reduce_all': True})
return reduce_out, hidden
class SimpleRNN(fluid.imperative.Layer):
def __init__(self):
super(SimpleRNN, self).__init__()

21
python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py
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@ -0,0 +1,21 @@
# 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 unittest
import paddle.fluid.framework as framework
import paddle.fluid.optimizer as optimizer
from paddle.fluid.backward import append_backward
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