eq to equal

deepspeech/modules/attention.py

@@ -98,7 +98,8 @@ class MultiHeadedAttention(nn.Layer):
         """
         n_batch = value.shape[0]
         if mask is not None:
-            mask = mask.unsqueeze(1).eq(0)  # (batch, 1, *, time2)
+            mask = mask.unsqueeze(1).equal(
+                paddle.to_tensor(0, dtype=mask.dtype))  # (batch, 1, *, time2)
             scores = scores.masked_fill(mask, -float('inf'))
             attn = paddle.softmax(
                 scores, axis=-1).masked_fill(mask,
@@ -109,8 +110,8 @@ class MultiHeadedAttention(nn.Layer):
 
         p_attn = self.dropout(attn)
         x = paddle.matmul(p_attn, value)  # (batch, head, time1, d_k)
-        x = x.transpose([0, 2, 1, 3]).contiguous().reshape([
-            n_batch, -1, self.h * self.d_k])  # (batch, time1, d_model)
+        x = x.transpose([0, 2, 1, 3]).contiguous().reshape(
+            [n_batch, -1, self.h * self.d_k])  # (batch, time1, d_model)
 
         return self.linear_out(x)  # (batch, time1, d_model)