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import numpy as np
from hypothesis import given, assume
import hypothesis.strategies as st
from caffe2.python import core, model_helper, utils
import caffe2.python.hypothesis_test_util as hu
class TestLeakyRelu(hu.HypothesisTestCase):
def _get_inputs(self, N, C, H, W, order):
input_data = np.random.rand(N, C, H, W).astype(np.float32) - 0.5
# default step size is 0.05
input_data[np.logical_and(
input_data >= 0, input_data <= 0.051)] = 0.051
input_data[np.logical_and(
input_data <= 0, input_data >= -0.051)] = -0.051
if order == 'NHWC':
input_data = utils.NCHW2NHWC(input_data)
return input_data,
def _get_op(self, device_option, alpha, order, inplace=False):
outputs = ['output' if not inplace else "input"]
op = core.CreateOperator(
'LeakyRelu',
['input'],
outputs,
alpha=alpha,
device_option=device_option)
return op
def _feed_inputs(self, input_blobs, device_option):
names = ['input', 'scale', 'bias']
for name, blob in zip(names, input_blobs):
self.ws.create_blob(name).feed(blob, device_option=device_option)
@given(gc=hu.gcs['gc'],
dc=hu.gcs['dc'],
N=st.integers(2, 3),
C=st.integers(2, 3),
H=st.integers(2, 3),
W=st.integers(2, 3),
alpha=st.floats(0, 1),
order=st.sampled_from(['NCHW', 'NHWC']),
seed=st.integers(0, 1000))
def test_leaky_relu_gradients(self, gc, dc, N, C, H, W, order, alpha, seed):
np.random.seed(seed)
op = self._get_op(
device_option=gc,
alpha=alpha,
order=order)
input_blobs = self._get_inputs(N, C, H, W, order)
self.assertDeviceChecks(dc, op, input_blobs, [0])
self.assertGradientChecks(gc, op, input_blobs, 0, [0])
@given(gc=hu.gcs['gc'],
dc=hu.gcs['dc'],
N=st.integers(2, 10),
C=st.integers(3, 10),
H=st.integers(5, 10),
W=st.integers(7, 10),
alpha=st.floats(0, 1),
seed=st.integers(0, 1000))
def test_leaky_relu_layout(self, gc, dc, N, C, H, W, alpha, seed):
outputs = {}
for order in ('NCHW', 'NHWC'):
np.random.seed(seed)
input_blobs = self._get_inputs(N, C, H, W, order)
self._feed_inputs(input_blobs, device_option=gc)
op = self._get_op(
device_option=gc,
alpha=alpha,
order=order)
self.ws.run(op)
outputs[order] = self.ws.blobs['output'].fetch()
np.testing.assert_allclose(
outputs['NCHW'],
utils.NHWC2NCHW(outputs["NHWC"]),
atol=1e-4,
rtol=1e-4)
@given(gc=hu.gcs['gc'],
dc=hu.gcs['dc'],
N=st.integers(2, 10),
C=st.integers(3, 10),
H=st.integers(5, 10),
W=st.integers(7, 10),
order=st.sampled_from(['NCHW', 'NHWC']),
alpha=st.floats(0, 1),
seed=st.integers(0, 1000),
inplace=st.booleans())
def test_leaky_relu_reference_check(self, gc, dc, N, C, H, W, order, alpha,
seed, inplace):
np.random.seed(seed)
if order != "NCHW":
assume(not inplace)
inputs = self._get_inputs(N, C, H, W, order)
op = self._get_op(
device_option=gc,
alpha=alpha,
order=order,
inplace=inplace)
def ref(input_blob):
result = input_blob.copy()
result[result < 0] *= alpha
return result,
self.assertReferenceChecks(gc, op, inputs, ref)
@given(gc=hu.gcs['gc'],
dc=hu.gcs['dc'],
N=st.integers(2, 10),
C=st.integers(3, 10),
H=st.integers(5, 10),
W=st.integers(7, 10),
order=st.sampled_from(['NCHW', 'NHWC']),
alpha=st.floats(0, 1),
seed=st.integers(0, 1000))
def test_leaky_relu_device_check(self, gc, dc, N, C, H, W, order, alpha,
seed):
np.random.seed(seed)
inputs = self._get_inputs(N, C, H, W, order)
op = self._get_op(
device_option=gc,
alpha=alpha,
order=order)
self.assertDeviceChecks(dc, op, inputs, [0])
@given(N=st.integers(2, 10),
C=st.integers(3, 10),
H=st.integers(5, 10),
W=st.integers(7, 10),
order=st.sampled_from(['NCHW', 'NHWC']),
alpha=st.floats(0, 1),
seed=st.integers(0, 1000))
def test_leaky_relu_model_helper_helper(self, N, C, H, W, order, alpha, seed):
np.random.seed(seed)
arg_scope = {'order': order}
model = model_helper.ModelHelper(name="test_model", arg_scope=arg_scope)
model.LeakyRelu(
'input',
'output',
alpha=alpha)
input_blob = np.random.rand(N, C, H, W).astype(np.float32)
if order == 'NHWC':
input_blob = utils.NCHW2NHWC(input_blob)
self.ws.create_blob('input').feed(input_blob)
self.ws.create_net(model.param_init_net).run()
self.ws.create_net(model.net).run()
output_blob = self.ws.blobs['output'].fetch()
if order == 'NHWC':
output_blob = utils.NHWC2NCHW(output_blob)
assert output_blob.shape == (N, C, H, W)
if __name__ == '__main__':
import unittest
unittest.main()
|
