Convolution Calculator

Input Width:

Input Height:

Input Channels:

Kernel Size:

Padding:

Stride:

Output Channels:

Output Size: 0 x 0 x 1

After Flattening: 0

PyTorch

torch.nn.Conv2d(in_channels = 1, out_channels = 1, kernel_size = 1, stride=1, padding=0)

Keras

tf.keras.layers.Conv2D(filters = 1, kernel_size = 1, strides = 1, padding = valid)

Input Width:

Input Height:

Input Channels:

Kernel Size:

Padding: (Usually 0 in pooling)

Stride:

Output Channels: