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111 lines
3.0 KiB
111 lines
3.0 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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from op_test import OpTest
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def fc_refer(matrix, with_bias):
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in_n, in_c, in_h, in_w = matrix.input.shape
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w_i, w_o = matrix.weights.shape
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x_data = np.reshape(matrix.input, [in_n, in_c * in_h * in_w])
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w_data = np.reshape(matrix.weights, [w_i, w_o])
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b_data = np.reshape(matrix.bias, [1, w_o])
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result = None
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if with_bias:
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result = np.dot(x_data, w_data) + b_data
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else:
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result = np.dot(x_data, w_data)
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return result
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class MatrixGenerate:
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def __init__(self, mb, ic, oc, h, w):
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self.input = np.random.random((mb, ic, h, w)).astype("float32")
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self.weights = np.random.random((ic * h * w, oc)).astype("float32")
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self.bias = np.random.random((1, oc)).astype("float32")
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class TestFCOp(OpTest):
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def setUp(self):
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self.op_type = "fc"
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self.matrix = MatrixGenerate(1, 10, 15, 3, 3)
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self.with_bias = True
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if self.with_bias:
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self.inputs = {
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'Input': self.matrix.input,
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'W': self.matrix.weights,
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'Bias': self.matrix.bias
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}
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else:
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self.inputs = {'Input': self.matrix.input, 'W': self.matrix.weights}
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self.attrs = {'use_mkldnn': False}
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self.outputs = {'Out': fc_refer(self.matrix, self.with_bias)}
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def test_check_output(self):
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self.check_output()
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class TestFCOpNoBias(TestFCOp):
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def init_shapes(self, mb, ic, oc, h, w):
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self.with_bias = False
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self.matrix = MatrixGenerate(mb, ic, oc, h, w)
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class TestFCOpWithBias(TestFCOp):
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def init_shapes(self, mb, ic, oc, h, w):
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self.with_bias = True
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self.matrix = MatrixGenerate(mb, ic, oc, h, w)
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class TestFCOp1(TestFCOpNoBias):
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def init_op_type(self):
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self.init_shapes(2, 8, 10, 1, 1)
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class TestFCOp2(TestFCOpNoBias):
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def init_op_type(self):
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self.init_shapes(4, 5, 6, 2, 2)
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class TestFCOp4(TestFCOpNoBias):
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def init_op_type(self):
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self.init_shapes(1, 32, 64, 3, 3)
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class TestFCOpWithBias1(TestFCOpWithBias):
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def init_op_type(self):
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self.init_shapes(3, 8, 10, 2, 1)
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class TestFCOpWithBias2(TestFCOpWithBias):
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def init_op_type(self):
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self.init_shapes(4, 5, 6, 2, 2)
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class TestFCOpWithBias3(TestFCOpWithBias):
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def init_op_type(self):
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self.init_shapes(1, 64, 32, 3, 3)
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if __name__ == "__main__":
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unittest.main()
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