未验证 提交 146ed409 编写于 作者: J joanna.wozna.intel 提交者: GitHub

Add test with reused requantize op (#22482)

test=develop
上级 96770f51
......@@ -16,6 +16,8 @@ from __future__ import print_function
import unittest
import numpy as np
import paddle.fluid as fluid
import paddle.fluid.core as core
from paddle.fluid.tests.unittests.op_test import OpTest
from mkldnn_op_test import format_reorder
......@@ -25,29 +27,31 @@ class TestReQuantizeOp(OpTest):
self.op_type = 'requantize'
self.scale_in = 2.0
self.scale_out = 1.5
self.input_size = [1, 1, 5, 5]
self.input_size = [1, 1, 10, 10]
self.data_type = 'int8'
self.set_scale()
self.set_data_type()
self.prepare_inputs()
def prepare_inputs(self):
scale_shift = self.scale_out / self.scale_in
if self.data_type == 'int8':
input = (np.random.randint(0, 100, self.input_size) - 50
).astype(self.data_type)
output_tmp = np.round(input.astype('float32') *
self.input = (np.random.randint(0, 100, self.input_size) - 50
).astype(self.data_type)
output_tmp = np.round(self.input.astype('float32') *
scale_shift).astype('int8')
else:
input = (np.random.randint(0, 100,
self.input_size)).astype(self.data_type)
output_tmp = np.round(input.astype('float32') *
self.input = (np.random.randint(
0, 100, self.input_size)).astype(self.data_type)
output_tmp = np.round(self.input.astype('float32') *
scale_shift).astype('uint8')
output = format_reorder(output_tmp, self.input_size)
self.output = format_reorder(output_tmp, self.input_size)
self.inputs = {'Input': OpTest.np_dtype_to_fluid_dtype(input)}
self.inputs = {'Input': OpTest.np_dtype_to_fluid_dtype(self.input)}
self.outputs = {'Output': output}
self.outputs = {'Output': self.output}
self.attrs = {'Scale_in': self.scale_in, 'Scale_out': self.scale_out}
......@@ -90,5 +94,48 @@ class TestReQuantizeOp4(TestReQuantizeOp2):
self.data_type = 'uint8'
#-------------------test reused requantize op---------------------------
class TestReQuantizeOpReused(TestReQuantizeOp):
def setUp(self):
self.input_size = [1, 1, 10, 10]
self.data_type = 'int8'
self.set_scale()
self.prepare_inputs()
def set_scale(self):
self.scale_in = 0.1
self.scale_out = 0.2
def test_check_output(self):
variables = {
"input": self.input,
"output": self.output,
}
program = fluid.Program()
with fluid.program_guard(program):
block = program.global_block()
for name in variables:
block.create_var(
name=name, dtype="int8", shape=variables[name].shape)
requant_op = block.append_op(
type="requantize",
inputs={'Input': block.var('input'), },
outputs={"Output": block.var('output')},
attrs={'Scale_in': self.scale_in,
'Scale_out': self.scale_out})
place = core.CPUPlace()
exe = fluid.Executor(place)
for i in range(2):
out = exe.run(program,
feed={'input': variables['input']},
fetch_list=['output'])
self.assertTrue(
np.allclose(
variables['output'], out[0], atol=1e-4), 'output')
if __name__ == '__main__':
unittest.main()
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