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@ -16,6 +16,8 @@ from __future__ import print_function
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import unittest
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import numpy as np
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import paddle.fluid as fluid
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import paddle.fluid.core as core
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from paddle.fluid.tests.unittests.op_test import OpTest
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from mkldnn_op_test import format_reorder
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@ -25,29 +27,31 @@ class TestReQuantizeOp(OpTest):
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self.op_type = 'requantize'
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self.scale_in = 2.0
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self.scale_out = 1.5
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self.input_size = [1, 1, 5, 5]
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self.input_size = [1, 1, 10, 10]
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self.data_type = 'int8'
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self.set_scale()
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self.set_data_type()
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self.prepare_inputs()
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def prepare_inputs(self):
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scale_shift = self.scale_out / self.scale_in
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if self.data_type == 'int8':
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input = (np.random.randint(0, 100, self.input_size) - 50
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).astype(self.data_type)
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output_tmp = np.round(input.astype('float32') *
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self.input = (np.random.randint(0, 100, self.input_size) - 50
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).astype(self.data_type)
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output_tmp = np.round(self.input.astype('float32') *
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scale_shift).astype('int8')
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else:
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input = (np.random.randint(0, 100,
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self.input_size)).astype(self.data_type)
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output_tmp = np.round(input.astype('float32') *
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self.input = (np.random.randint(
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0, 100, self.input_size)).astype(self.data_type)
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output_tmp = np.round(self.input.astype('float32') *
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scale_shift).astype('uint8')
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output = format_reorder(output_tmp, self.input_size)
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self.output = format_reorder(output_tmp, self.input_size)
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self.inputs = {'Input': OpTest.np_dtype_to_fluid_dtype(input)}
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self.inputs = {'Input': OpTest.np_dtype_to_fluid_dtype(self.input)}
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self.outputs = {'Output': output}
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self.outputs = {'Output': self.output}
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self.attrs = {'Scale_in': self.scale_in, 'Scale_out': self.scale_out}
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@ -90,5 +94,48 @@ class TestReQuantizeOp4(TestReQuantizeOp2):
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self.data_type = 'uint8'
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#-------------------test reused requantize op---------------------------
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class TestReQuantizeOpReused(TestReQuantizeOp):
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def setUp(self):
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self.input_size = [1, 1, 10, 10]
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self.data_type = 'int8'
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self.set_scale()
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self.prepare_inputs()
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def set_scale(self):
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self.scale_in = 0.1
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self.scale_out = 0.2
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def test_check_output(self):
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variables = {
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"input": self.input,
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"output": self.output,
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}
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program = fluid.Program()
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with fluid.program_guard(program):
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block = program.global_block()
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for name in variables:
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block.create_var(
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name=name, dtype="int8", shape=variables[name].shape)
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requant_op = block.append_op(
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type="requantize",
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inputs={'Input': block.var('input'), },
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outputs={"Output": block.var('output')},
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attrs={'Scale_in': self.scale_in,
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'Scale_out': self.scale_out})
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place = core.CPUPlace()
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exe = fluid.Executor(place)
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for i in range(2):
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out = exe.run(program,
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feed={'input': variables['input']},
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fetch_list=['output'])
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self.assertTrue(
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np.allclose(
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variables['output'], out[0], atol=1e-4), 'output')
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if __name__ == '__main__':
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unittest.main()
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