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def conv_forward(A_prev, W, b, hparameters): | |
""" | |
Implements the forward propagation for a convolution function | |
Arguments: | |
A_prev -- output activations of the previous layer, | |
numpy array of shape (m, n_H_prev, n_W_prev, n_C_prev) | |
W -- Weights, numpy array of shape (f, f, n_C_prev, n_C) | |
b -- Biases, numpy array of shape (1, 1, 1, n_C) | |
hparameters -- python dictionary containing "stride" and "pad" |