def question_1i_sanity_check():
""" Sanity check for word Convolution layer
"""
input = torch.randn((10, 50, 20)) #(B, word_num, char_embed, char_num)
kernel_size = 5
cnn = CNN(20, 50, 300, kernel_size)
conved = cnn.conv(input)
assert conved.shape == (10, 300, 16)
pooled = torch.squeeze(cnn.pooling(conved))
assert pooled.shape == (10, 300)
print("-" * 80)
print("Sanity Check Passed for Question 1i: CNN")
