提交 a6aa782e 编写于 作者: P phlrain

add unitest

上级 3f4aca61
# 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 numpy as np
import paddle.fluid.core as core
from op_test import OpTest
def lstm_naive(
input,
w, ):
seq_len, batch_size, hidden_size = input.shape
offset = 0
wi = w[offset:offset + hidden_size * hidden_size].reshape(
(hidden_size, hidden_size)).transpose()
offset += hidden_size * hidden_size
wf = w[offset:offset + hidden_size * hidden_size].reshape(
(hidden_size, hidden_size)).transpose()
offset += hidden_size * hidden_size
wc = w[offset:offset + hidden_size * hidden_size].reshape(
(hidden_size, hidden_size)).transpose()
offset += hidden_size * hidden_size
wo = w[offset:offset + hidden_size * hidden_size].reshape(
(hidden_size, hidden_size)).transpose()
offset += hidden_size * hidden_size
ri = w[offset:offset + hidden_size * hidden_size].reshape(
(hidden_size, hidden_size)).transpose()
offset += hidden_size * hidden_size
rf = w[offset:offset + hidden_size * hidden_size].reshape(
(hidden_size, hidden_size)).transpose()
offset += hidden_size * hidden_size
rc = w[offset:offset + hidden_size * hidden_size].reshape(
(hidden_size, hidden_size)).transpose()
offset += hidden_size * hidden_size
ro = w[offset:offset + hidden_size * hidden_size].reshape(
(hidden_size, hidden_size)).transpose()
offset += hidden_size * hidden_size
bi_1 = w[offset:offset + hidden_size]
offset += hidden_size
bf_1 = w[offset:offset + hidden_size]
offset += hidden_size
bc_1 = w[offset:offset + hidden_size]
offset += hidden_size
bo_1 = w[offset:offset + hidden_size]
offset += hidden_size
bi_2 = w[offset:offset + hidden_size]
offset += hidden_size
bf_2 = w[offset:offset + hidden_size]
offset += hidden_size
bc_2 = w[offset:offset + hidden_size]
offset += hidden_size
bo_2 = w[offset:offset + hidden_size]
def sigmoid(x):
return 1.0 / (1.0 + np.exp(-x))
def tanh(x):
return (np.exp(x) - np.exp(-x)) / (np.exp(x) + np.exp(-x))
output = []
pre_h = np.zeros((batch_size, hidden_size), dtype=input.dtype)
pre_c = np.zeros((batch_size, hidden_size), dtype=input.dtype)
for i in range(seq_len):
emb_1 = input[i]
input_gate = sigmoid(
np.matmul(emb_1, wi) + np.matmul(pre_h, ri) + bi_1 + bi_2)
forget_gate = sigmoid(
np.matmul(emb_1, wf) + np.matmul(pre_h, rf) + bf_1 + bf_2)
output_gate = sigmoid(
np.matmul(emb_1, wo) + np.matmul(pre_h, ro) + bo_1 + bo_2)
c_t_temp = tanh(
np.matmul(emb_1, wc) + np.matmul(pre_h, rc) + bc_1 + bc_2)
new_c = input_gate * c_t_temp + forget_gate * pre_c
new_h = output_gate * tanh(new_c)
pre_h = new_h
pre_c = new_c
output.append(new_h)
output = np.concatenate(output, -1)
output = output.reshape((batch_size, -1, hidden_size))
output = output.transpose((1, 0, 2))
return output
class TestCUDNNLstmOp(OpTest):
def setUp(self):
self.op_type = "cudnn_lstm"
self.dtype = np.float32
num_steps = 50
batch_size = 20
hidden_size = 200
input_weight_size = (hidden_size * hidden_size) * 4
hidden_weight_size = (hidden_size * hidden_size) * 4
weight_size = input_weight_size + hidden_weight_size
weight_size += hidden_size * 8
input = np.random.random(
(num_steps, batch_size, hidden_size)).astype(self.dtype)
flat_w = np.random.random((weight_size)).astype(self.dtype)
output = lstm_naive(input, flat_w)
init_h = np.zeros((batch_size, hidden_size), dtype=np.float32)
init_c = np.zeros((batch_size, hidden_size), dtype=np.float32)
self.inputs = {
'Input': OpTest.np_dtype_to_fluid_dtype(input),
'W': OpTest.np_dtype_to_fluid_dtype(flat_w),
'InitH': OpTest.np_dtype_to_fluid_dtype(init_h),
'InitC': OpTest.np_dtype_to_fluid_dtype(init_c),
}
self.attrs = {
'max_len': num_steps,
'dropout_prob': 0.0,
'is_bidirec': False,
'input_size': hidden_size,
'hidden_size': hidden_size,
'num_layers': 1,
}
self.outputs = {'Out': output}
def test_grad_with_place(self):
place = core.CUDAPlace(0)
self.check_grad_with_place(place, atol=1e-5)
def test_output_with_place(self):
place = core.CUDAPlace(0)
self.check_output_with_place(
place, atol=1e-5, no_check_set=['last_h', 'last_c'])
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