def question_1i_sanity_check():
""" Sanity check for cnn.
"""
print ("-"*80)
print("Running Sanity Check for Question 1i: Cnn")
print ("-"*80)
# TODO: write test cases
emb_size = 2
cnn = CNN(2, emb_size, kernel_size=2)
# out_channels, in_channels, kernel_size
cnn.cnn.weight.data = torch.Tensor([[[1, -1], [-1, 1]],
[[0.1, 0.2], [-0.3, 0.05]]])
cnn.cnn.bias.data = torch.zeros(emb_size)
# validate input & output shape
inpt = torch.Tensor([[[0.1, 0.2, 0, 0], [0, 1.3, 0, 0]]])
batch_size = inpt.size()[0]
output_expected_size = [batch_size, emb_size]
output = cnn(inpt)
assert(list(output.size()) == output_expected_size), "output shape is incorrect: it should be:\n {} but is:\n{}".format(output_expected_size, list(output.size()))
after_relu = F.relu(cnn.cnn(inpt))
expected_after_relu = torch.Tensor([[1.2, 0, 0], [0.115, 0, 0]])
assert(after_relu.allclose(expected_after_relu)), "after_relu is incorrect: it should be:\n {} but is:\n{}".format(expected_after_relu, after_relu)
expected_output = torch.Tensor([[1.2, 0.115]])
assert(output.allclose(expected_output)), "output is incorrect: it should be:\n {} but is:\n{}".format(expected_output, output)
print("Sanity Check Passed for Question 1i: Cnn!")
print("-"*80)
