def mypad(x, pad, mode='constant', value=0):
if mode == 'symmetric':
# Horizontal only
if pad[0] == 0 and pad[1] == 0:
m1, m2 = pad[2], pad[3]
l = x.shape[-2]
xe = reflect(np.arange(-m1, l + m2, dtype='int32'), -0.5, l - 0.5)
return x[:, :, xe]
# Vertical only
elif pad[2] == 0 and pad[3] == 0:
m1, m2 = pad[0], pad[1]
l = x.shape[-1]
xe = reflect(np.arange(-m1, l + m2, dtype='int32'), -0.5, l - 0.5)
return x[:, :, :, xe]
# Both
else:
m1, m2 = pad[0], pad[1]
l1 = x.shape[-1]
xe_row = reflect(np.arange(-m1, l1 + m2, dtype='int32'), -0.5,
l1 - 0.5)
m1, m2 = pad[2], pad[3]
l2 = x.shape[-2]
xe_col = reflect(np.arange(-m1, l2 + m2, dtype='int32'), -0.5,
l2 - 0.5)
i = np.outer(xe_col, np.ones(xe_row.shape[0]))
j = np.outer(np.ones(xe_col.shape[0]), xe_row)
return x[:, :, i, j]
elif mode == 'constant' or mode == 'reflect' or mode == 'replicate':
return F.pad(x, pad, mode, value)
elif mode == 'zero':
return F.pad(x, pad)
else:
raise ValueError("Unkown pad type: {}".format(mode))
def mypad(x, pad, mode='constant', value=0):
""" Function to do numpy like padding on tensors. Only works for 2-D
padding.
Inputs:
x (tensor): tensor to pad
pad (tuple): tuple of (left, right, top, bottom) pad sizes
mode (str): 'symmetric', 'wrap', 'constant, 'reflect', 'replicate', or
'zero'. The padding technique.
"""
if mode == 'symmetric':
# Vertical only
if pad[0] == 0 and pad[1] == 0:
m1, m2 = pad[2], pad[3]
l = x.shape[-2]
xe = reflect(np.arange(-m1, l+m2, dtype='int32'), -0.5, l-0.5)
return x[:,:,xe]
# horizontal only
elif pad[2] == 0 and pad[3] == 0:
m1, m2 = pad[0], pad[1]
l = x.shape[-1]
xe = reflect(np.arange(-m1, l+m2, dtype='int32'), -0.5, l-0.5)
return x[:,:,:,xe]
# Both
else:
m1, m2 = pad[0], pad[1]
l1 = x.shape[-1]
xe_row = reflect(np.arange(-m1, l1+m2, dtype='int32'), -0.5, l1-0.5)
m1, m2 = pad[2], pad[3]
l2 = x.shape[-2]
xe_col = reflect(np.arange(-m1, l2+m2, dtype='int32'), -0.5, l2-0.5)
i = np.outer(xe_col, np.ones(xe_row.shape[0]))
j = np.outer(np.ones(xe_col.shape[0]), xe_row)
return x[:,:,i,j]
elif mode == 'periodic':
# Vertical only
if pad[0] == 0 and pad[1] == 0:
xe = np.arange(x.shape[-2])
xe = np.pad(xe, (pad[2], pad[3]), mode='wrap')
return x[:,:,xe]
# Horizontal only
elif pad[2] == 0 and pad[3] == 0:
xe = np.arange(x.shape[-1])
xe = np.pad(xe, (pad[0], pad[1]), mode='wrap')
return x[:,:,:,xe]
# Both
else:
xe_col = np.arange(x.shape[-2])
xe_col = np.pad(xe_col, (pad[2], pad[3]), mode='wrap')
xe_row = np.arange(x.shape[-1])
xe_row = np.pad(xe_row, (pad[0], pad[1]), mode='wrap')
i = np.outer(xe_col, np.ones(xe_row.shape[0]))
j = np.outer(np.ones(xe_col.shape[0]), xe_row)
return x[:,:,i,j]
elif mode == 'constant' or mode == 'reflect' or mode == 'replicate':
return F.pad(x, pad, mode, value)
elif mode == 'zero':
return F.pad(x, pad)
else:
raise ValueError("Unkown pad type: {}".format(mode))