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refactor ut part 3 (PaddlePaddle#291)
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* refactor ut part 3

* update

* update
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@XBWGC
XBWGC authored Nov 16, 2021
1 parent 7611254 commit 6f51e1f
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Showing 21 changed files with 881 additions and 1,070 deletions.
2 changes: 0 additions & 2 deletions python/paddle/fluid/tests/unittests/ipu/test_ipu_shard_api.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,9 +16,7 @@

import numpy as np
import unittest
import sys
import paddle
import paddle.fluid as fluid

paddle.enable_static()

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57 changes: 0 additions & 57 deletions python/paddle/fluid/tests/unittests/ipu/test_ipu_strategy.py
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111 changes: 58 additions & 53 deletions python/paddle/fluid/tests/unittests/ipu/test_layernorm_op_ipu.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,14 +16,9 @@

import numpy as np
import paddle
import paddle.fluid as fluid
import paddle.fluid.compiler as compiler
import paddle.optimizer
import paddle.static
from paddle.fluid.tests.unittests.ipu.op_test_ipu import (IPUOpTest,
np_dtype_to_fluid_str)

paddle.enable_static()
import paddle.fluid.contrib.mixed_precision.fp16_utils as fp16_utils
from paddle.fluid.tests.unittests.ipu.op_test_ipu import IPUOpTest, ExecutionMode


@unittest.skipIf(not paddle.is_compiled_with_ipu(),
Expand All @@ -32,26 +27,31 @@ class TestBase(IPUOpTest):
def setUp(self):
self.set_atol()
self.set_training()
self.set_feed()
self.set_data_feed()
self.set_feed_attr()
self.set_attrs()
self.set_op_attrs()

@property
def fp16_enabled(self):
return True

def set_atol(self):
self.atol = 1e-6
self.rtol = 1e-5
self.atol_fp16 = 1e-2
self.rtol_fp16 = 1e-3

def set_feed(self):
self.feed = {
"x": np.random.uniform(size=[1, 3, 10, 10]).astype('float32'),
}
def set_data_feed(self):
x = np.random.uniform(size=[1, 3, 10, 10])
self.feed_fp32 = {"x": x.astype(np.float32)}
self.feed_fp16 = {"x": x.astype(np.float16)}

def set_feed_attr(self):
self.feed_shape = [x.shape for x in self.feed.values()]
self.feed_list = list(self.feed.keys())
self.feed_dtype = [
np_dtype_to_fluid_str(x.dtype) for x in self.feed.values()
]
self.feed_shape = [x.shape for x in self.feed_fp32.values()]
self.feed_list = list(self.feed_fp32.keys())
self.feed_dtype = [x.dtype for x in self.feed_fp32.values()]

def set_attrs(self):
def set_op_attrs(self):
self.attrs = {
"scale": True,
"shift": True,
Expand All @@ -60,37 +60,39 @@ def set_attrs(self):
}
self.optimizer = None

def _test_base(self, run_ipu=True):
scope = fluid.core.Scope()
def _test_base(self, exec_mode):
scope = paddle.fluid.core.Scope()
main_prog = paddle.static.Program()
startup_prog = paddle.static.Program()
SEED = self.SEED
main_prog.random_seed = SEED
startup_prog.random_seed = SEED
main_prog.random_seed = self.SEED
startup_prog.random_seed = self.SEED

with fluid.scope_guard(scope):
with paddle.fluid.scope_guard(scope):
with paddle.static.program_guard(main_prog, startup_prog):
x = paddle.static.data(
name=self.feed_list[0],
shape=self.feed_shape[0],
dtype=self.feed_dtype[0])
dtype='float32')

with paddle.static.amp.fp16_guard():
if self.is_training:
ch = self.feed_shape[0][1]
conv1 = paddle.static.nn.conv2d(
x, num_filters=ch, filter_size=3, bias_attr=False)
scale = paddle.ParamAttr(trainable=True)
bias = paddle.ParamAttr(trainable=True)
out = paddle.fluid.layers.nn.layer_norm(
conv1,
param_attr=scale,
bias_attr=bias,
**self.attrs)
else:
scale = self.attrs['scale']
bias = self.attrs['shift']
out = paddle.fluid.layers.nn.layer_norm(
x, param_attr=scale, bias_attr=bias, **self.attrs)
loss = paddle.mean(out)

if self.is_training:
ch = self.feed_shape[0][1]
conv1 = paddle.static.nn.conv2d(
x, num_filters=ch, filter_size=3, bias_attr=False)
scale = paddle.ParamAttr(trainable=True)
bias = paddle.ParamAttr(trainable=True)
out = paddle.fluid.layers.nn.layer_norm(
conv1, param_attr=scale, bias_attr=bias, **self.attrs)
else:
# scale = True
# bias = True
scale = self.attrs['scale']
bias = self.attrs['shift']
out = paddle.fluid.layers.nn.layer_norm(
x, param_attr=scale, bias_attr=bias, **self.attrs)
loss = paddle.mean(out)
fetch_list = [loss.name]

if self.is_training:
Expand All @@ -102,16 +104,17 @@ def _test_base(self, run_ipu=True):
elif self.optimizer == 'lamb':
optimizer = paddle.optimizer.Lamb(
learning_rate=1e-2, lamb_weight_decay=0.0)
optimizer.minimize(loss)
if optimizer is not None:
optimizer.minimize(loss)

if run_ipu:
if exec_mode:
place = paddle.IPUPlace()
else:
place = paddle.CPUPlace()
exe = paddle.static.Executor(place)
exe.run(startup_prog)

if run_ipu:
if exec_mode:
feed_list = self.feed_list
ipu_strategy = compiler.get_ipu_strategy()
ipu_strategy.is_training = self.is_training
Expand All @@ -125,12 +128,14 @@ def _test_base(self, run_ipu=True):
result = []
for _ in range(self.epoch):
loss_res = exe.run(program,
feed=self.feed,
feed=self.feed_fp32,
fetch_list=fetch_list)
result.append(loss_res[0])
return np.array(result)
else:
result = exe.run(program, feed=self.feed, fetch_list=fetch_list)
result = exe.run(program,
feed=self.feed_fp32,
fetch_list=fetch_list)
return result[0]

def test_base(self):
Expand All @@ -146,7 +151,7 @@ def test_base(self):

@unittest.skip('raise error')
class TestCase1(TestBase):
def set_attrs(self):
def set_op_attrs(self):
self.attrs = {
"scale": False,
"shift": True,
Expand All @@ -157,7 +162,7 @@ def set_attrs(self):

@unittest.skip('raise error')
class TestCase2(TestBase):
def set_attrs(self):
def set_op_attrs(self):
self.attrs = {
"scale": True,
"shift": False,
Expand All @@ -167,7 +172,7 @@ def set_attrs(self):


class TestCase3(TestBase):
def set_attrs(self):
def set_op_attrs(self):
self.attrs = {
"scale": True,
"shift": True,
Expand All @@ -178,7 +183,7 @@ def set_attrs(self):


class TestTrainCase1(TestBase):
def set_attrs(self):
def set_op_attrs(self):
self.attrs = {
"scale": True,
"shift": True,
Expand All @@ -199,7 +204,7 @@ class TestTrainCase2(TestBase):
def set_atol(self):
self.atol = 5e-4

def set_attrs(self):
def set_op_attrs(self):
self.attrs = {
"scale": True,
"shift": True,
Expand All @@ -217,7 +222,7 @@ class TestTrainCase3(TestBase):
def set_atol(self):
self.atol = 5e-3

def set_attrs(self):
def set_op_attrs(self):
self.attrs = {
"scale": True,
"shift": True,
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