import numpy as np
"""
FGGen模型中的PosEncoding
"""
def GetPosEncodingMatrix(max_len, d_emb):
'''
对应文章中的使用sine和consine function去做positional encodings
PE（pos,2i）= sin(pos/10000^2i/dmodel)
'''
pos_enc = np.array([
[pos / np.power(10000, 2 * (j // 2) / d_emb) for j in range(d_emb)]
if pos != 0 else np.zeros(d_emb)
for pos in range(max_len)
])
pos_enc[1:, 0::2] = np.sin(pos_enc[1:, 0::2]) # dim 2i
pos_enc[1:, 1::2] = np.cos(pos_enc[1:, 1::2]) # dim 2i+1
return pos_enc
def GetPosEncodingMatrix_myself(max_len, d_emb):
# PE（pos,2i）= sin(pos/10000^2i/dmodel)
pos_enc = []
for pos in range(max_len):
row = [pos / np.power(10000, 2 * (j // 2) / d_emb) for j in range(d_emb)]
pos_enc.append(row)
pos_enc = np.array(pos_enc)
pos_enc[1:, 0::2] = np.sin(pos_enc[1:, 0::2]) # dim 2i
pos_enc[1:, 1::2] = np.cos(pos_enc[1:, 1::2]) # dim 2i+1
return pos_enc
if __name__ =="__main__":
value1 = GetPosEncodingMatrix(60, 512)
value2 = GetPosEncodingMatrix_myself(60, 512)
equal_cnt = 0
for i in range(value1.shape[0]):
for j in range(value1.shape[1]):
if value1[i][j] == value2[i][j]:
equal_cnt += 1
else:
print("Error")
print(equal_cnt)
