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mrq 2024-05-11 17:34:45 -05:00
parent 88e9b9caff
commit a755eb3c62
1 changed files with 3 additions and 3 deletions
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vall_e/models/base.py
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@ -207,13 +207,13 @@ try:
if self.mode == "xformers": if self.mode == "xformers":
if attention_mask is None or attention_mask[0, 0, 0, 1] == 0: if attention_mask is None or attention_mask[0, 0, 0, 1] == 0:
attn_output = memory_efficient_attention(query_states, key_states, value_states, attn_bias=None) attn_output = memory_efficient_attention(query_states, key_states, value_states, attn_bias=None, p=dropout_rate)
else: else:
attn_output = memory_efficient_attention(query_states, key_states, value_states, attn_bias=LowerTriangularMask()) attn_output = memory_efficient_attention(query_states, key_states, value_states, attn_bias=LowerTriangularMask(), p=dropout_rate)
else: else:
#torch.nn.attention.sdpa_kernel #torch.nn.attention.sdpa_kernel
with torch.backends.cuda.sdp_kernel(enable_flash=self.mode == "flash", enable_math=self.mode == "math", enable_mem_efficient=self.mode == "mem_efficient"): with torch.backends.cuda.sdp_kernel(enable_flash=self.mode == "flash", enable_math=self.mode == "math", enable_mem_efficient=self.mode == "mem_efficient"):
attn_output = torch.nn.functional.scaled_dot_product_attention(query_states, key_states, value_states, attn_mask=attention_mask) attn_output = torch.nn.functional.scaled_dot_product_attention(query_states, key_states, value_states, attn_mask=attention_mask, dropout_p=dropout_rate)
attn_weights = None attn_weights = None