def test_maxpool2d_pads01(self):
import pytest
with pytest.raises(Exception) as e_info:
node = onnx.helper.make_node('MaxPool',
inputs=['x'],
outputs=['y'],
kernel_shape=[3, 3],
pads=[0, 0, 1, 1])
x = np.random.randn(1, 3, 28, 28).astype(np.float32)
x_shape = np.shape(x)
kernel_shape = (3, 3)
strides = (1, 1)
pad_top = pad_left = 0
pad_bottom = pad_right = 1
pad_shape = [pad_top + pad_bottom, pad_left + pad_right]
out_shape = pool_op_common.get_output_shape(
'VALID', np.add(x_shape[2:], pad_shape), kernel_shape, strides)
padded = np.pad(x, ((0, 0), (0, 0), (pad_top, pad_bottom),
(pad_left, pad_right)),
mode='constant',
constant_values=np.nan)
y = pool_op_common.pool(padded, x_shape, kernel_shape, strides,
out_shape, pad_shape, 'MAX')
output = OnnxLoader.run_node(node, [x])
np.testing.assert_almost_equal(output["y"], y, decimal=5)
def test_maxpool1d(self):
node = onnx.helper.make_node(
'MaxPool',
inputs=['x'],
outputs=['y'],
kernel_shape=[2],
)
x = np.random.randn(1, 3, 32).astype(np.float32)
x_shape = np.array(np.shape(x))
kernel_shape = np.array([2])
strides = [1]
out_shape = pool_op_common.get_output_shape('VALID', x_shape[2:], kernel_shape, strides)
padded = x
y = pool_op_common.pool(padded, x_shape, kernel_shape, strides, out_shape, [0], 'MAX')
output = OnnxLoader.run_node(node, [x])
np.testing.assert_almost_equal(output["y"], y, decimal=5)