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Add non square test to conv2d

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This commit is contained in:
Matúš Námešný
2024-05-23 21:50:39 +02:00
parent 37c29d6734
commit 78a0fd0baf
2 changed files with 272 additions and 40 deletions
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132
tools/conv2d_test.py
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@@ -128,9 +128,139 @@ def gen_convd_strided_test_result():
print_cpp_vector(output)
def gen_convd_non_square_input_test_result():
in_channels = 1
out_channels = 1
kernel_size = 2
stride = 1
padding = 0
input = torch.tensor([
0.946, 0.879, 0.382, 0.542, 0.453, 0.128,
0.128, 0.860, 0.778, 0.049, 0.974, 0.400,
0.400, 0.874, 0.161, 0.271, 0.580, 0.373,
0.078, 0.366, 0.396, 0.181, 0.246, 0.112,
]).reshape(1, 1, 4, 6)
weights = torch.tensor([
0.744, 0.745,
0.164, 0.157,
]).reshape(1, 1, 2, 2)
output = _conv2d(in_channels,
out_channels,
kernel_size,
stride,
padding,
input,
weights)
print_cpp_vector(output)
def gen_convd_non_square_kernel_test_result():
in_channels = 1
out_channels = 1
kernel_size = (1, 3)
stride = 1
padding = 0
input = torch.tensor([
0.946, 0.879, 0.382, 0.542,
0.128, 0.860, 0.778, 0.049,
0.400, 0.874, 0.161, 0.271,
0.078, 0.366, 0.396, 0.181
]).reshape(1, 1, 4, 4)
weights = torch.tensor([
0.744, 0.745, 0.164
]).reshape(1, 1, 1, 3)
output = _conv2d(in_channels,
out_channels,
kernel_size,
stride,
padding,
input,
weights)
print_cpp_vector(output)
def gen_convd_non_square_stride_test_result():
in_channels = 1
out_channels = 1
kernel_size = 2
stride = (1, 2)
padding = 0
input = torch.tensor([
0.946, 0.879, 0.382, 0.542,
0.128, 0.860, 0.778, 0.049,
0.400, 0.874, 0.161, 0.271,
0.078, 0.366, 0.396, 0.181
]).reshape(1, 1, 4, 4)
weights = torch.tensor([
0.144, 0.745,
0.964, 0.164
]).reshape(1, 1, 2, 2)
output = _conv2d(in_channels,
out_channels,
kernel_size,
stride,
padding,
input,
weights)
print_cpp_vector(output)
def gen_convd_non_square_padding_test_result():
in_channels = 1
out_channels = 1
kernel_size = 2
stride = 1
padding = (1, 2)
input = torch.tensor([
0.946, 0.879, 0.382, 0.542,
0.128, 0.860, 0.778, 0.049,
0.400, 0.874, 0.161, 0.271,
0.078, 0.366, 0.396, 0.181
]).reshape(1, 1, 4, 4)
weights = torch.tensor([
0.144, 0.745,
0.964, 0.164
]).reshape(1, 1, 2, 2)
output = _conv2d(in_channels,
out_channels,
kernel_size,
stride,
padding,
input,
weights)
print_cpp_vector(output)
if __name__ == "__main__":
print("Generating test results...")
print("Padded convolution test:")
gen_convd_padded_test_result()
print("Strided convolution test:")
gen_convd_strided_test_result()
gen_convd_strided_test_result()
print("Non square input convolution test:")
gen_convd_non_square_input_test_result()
print("Non square kernel convolution test:")
gen_convd_non_square_kernel_test_result()
print("Non square stride convolution test:")
gen_convd_non_square_stride_test_result()
print("Non square padding convolution test:")
gen_convd_non_square_padding_test_result()