def test_global_pooling_layer(self):
iX = XLayer(type=['Input'],
name='in1',
shapes=[1, 2, 7, 7],
sizes=[98],
bottoms=[],
tops=[],
targets=[])
X = xlf.get_xop_factory_func('GlobalPooling')(op_name='gp1',
pool_type='Max',
layout='NCHW',
input_layer=iX)
assert X.type[0] == 'Pooling'
assert X.shapes == [1, 2, 1, 1]
assert X.attrs['padding'] == [[0, 0], [0, 0], [0, 0], [0, 0]]
assert X.attrs['insize'] == [7, 7]
assert X.attrs['outsize'] == [1, 1]
assert X.attrs['data_layout'] == 'NCHW'
assert X.attrs['strides'] == [1, 1]
assert X.attrs['kernel_size'] == [7, 7]
assert X.attrs['pool_type'] == 'Max'
from pyxir.graph.ops.l2_convolution import \
pooling_layout_transform
pooling_layout_transform(X, target_layout='NHWC')
assert X.type[0] == 'Pooling'
assert X.shapes == [1, 1, 1, 2]
assert X.attrs['data_layout'] == 'NHWC'
def global_pool2d_test_util(
in_shape,
out_shape,
pool_type,
data_layout="NCHW",
):
iX = px.ops.input("in", shape=list(in_shape))
X = px.ops.global_pool2d(
op_name="pool",
input_layer=iX,
pool_type=pool_type,
layout=data_layout,
)
expected_padding = [[0, 0], [0, 0], [0, 0], [0, 0]]
layout_idx = tuple(["NCHW".index(e) for e in data_layout])
B_idx, C_idx, H_idx, W_idx = layout_idx
assert X.type[0] == "Pooling"
assert X.shapes == list(
out_shape), "Expected out shape: {0}, but got: {1}".format(
out_shape, X.shapes)
assert (X.attrs["padding"] == expected_padding
), "Expected padding: {0}, but got: {1}".format(
expected_padding, X.attrs["padding"])
assert X.attrs["insize"] == [in_shape[H_idx], in_shape[W_idx]]
assert X.attrs["outsize"] == [1, 1]
assert X.attrs["data_layout"] == data_layout
assert X.attrs["strides"] == [1, 1]
assert X.attrs["kernel_size"] == [in_shape[H_idx], in_shape[W_idx]]
assert X.attrs["pool_type"] == pool_type
# Test layout transform
pooling_layout_transform(X, target_layout="NHWC")
layout_idx = tuple([data_layout.index(e) for e in "NHWC"])
trans_layout_idx = tuple(["NCHW".index(e) for e in "NHWC"])
trans_out_shape = [out_shape[e] for e in layout_idx]
assert X.type[0] == "Pooling"
assert X.shapes == trans_out_shape, "Expected out shape: {0}, but got: {1}".format(
trans_out_shape, X.shapes)
assert X.attrs["data_layout"] == "NHWC"
assert (X.attrs["padding"] == expected_padding
), "Expected padding: {0}, but got: {1}".format(
expected_padding, X.attrs["padding"])
def test_pooling_layer(self):
iX = XLayer(type=['Input'],
name='in1',
shapes=[1, 2, 5, 5],
sizes=[50],
bottoms=[],
tops=[],
targets=[])
X = xlf.get_xop_factory_func('Pooling')(op_name='pool1',
input_layer=iX,
pool_type='Avg',
pool_size=[3, 3],
strides=[2, 2],
padding=[1, 1],
layout='NCHW',
ceil_mode=True,
count_include_pad=True)
assert X.type[0] == 'Pooling'
assert X.shapes == [1, 2, 3, 3]
assert X.attrs['padding'] == [[0, 0], [0, 0], [1, 1], [1, 1]]
assert X.attrs['insize'] == [5, 5]
assert X.attrs['outsize'] == [3, 3]
assert X.attrs['data_layout'] == 'NCHW'
assert X.attrs['strides'] == [2, 2]
assert X.attrs['kernel_size'] == [3, 3]
assert X.attrs['pool_type'] == 'Avg'
from pyxir.graph.ops.l2_convolution import \
pooling_layout_transform
pooling_layout_transform(X, target_layout='NHWC')
assert X.type[0] == 'Pooling'
assert X.shapes == [1, 3, 3, 2]
assert X.attrs['padding'] == [[0, 0], [1, 1], [1, 1], [0, 0]]
assert X.attrs['data_layout'] == 'NHWC'
def pool2d_test_util(
in_shape,
out_shape,
pool_type,
pool_size,
padding=(0, 0, 0, 0),
strides=(1, 1),
data_layout="NCHW",
):
iX = px.ops.input("in", shape=list(in_shape))
X = px.ops.pool2d(
op_name="pool",
input_layer=iX,
pool_type=pool_type,
pool_size=list(pool_size),
strides=list(strides),
padding=list(padding),
layout=data_layout,
ceil_mode=True,
count_include_pad=True,
)
layout_idx = tuple(["NCHW".index(e) for e in data_layout])
B_idx, C_idx, H_idx, W_idx = layout_idx
padding_nchw = [
[0, 0],
[0, 0],
[padding[0], padding[2]],
[padding[1], padding[3]],
]
padding = [padding_nchw[e] for e in layout_idx]
assert X.type[0] == "Pooling"
assert X.shapes == list(
out_shape), "Expected out shape: {0}, but got: {1}".format(
out_shape, X.shapes)
assert X.attrs[
"padding"] == padding, "Expected padding: {0}, but got: {1}".format(
padding, X.attrs["padding"])
assert X.attrs["insize"] == [in_shape[H_idx], in_shape[W_idx]]
assert X.attrs["outsize"] == [out_shape[H_idx], out_shape[W_idx]]
assert X.attrs["data_layout"] == data_layout
assert X.attrs["strides"] == list(strides)
assert X.attrs["kernel_size"] == list(pool_size)
assert X.attrs["pool_type"] == pool_type
# Test layout transform
pooling_layout_transform(X, target_layout="NHWC")
layout_idx = tuple([data_layout.index(e) for e in "NHWC"])
trans_layout_idx = tuple(["NCHW".index(e) for e in "NHWC"])
trans_out_shape = [out_shape[e] for e in layout_idx]
assert X.type[0] == "Pooling"
assert X.shapes == trans_out_shape, "Expected out shape: {0}, but got: {1}".format(
trans_out_shape, X.shapes)
assert X.attrs["data_layout"] == "NHWC"
padding = [padding_nchw[e] for e in trans_layout_idx]
assert X.attrs[
"padding"] == padding, "Expected padding: {0}, but got: {1}".format(
padding, X.attrs["padding"])