From 31c2c226cacf88281332e61bd03bb863b1c1e9cf Mon Sep 17 00:00:00 2001 From: zxcd <228587199@qq.com> Date: Mon, 30 Jan 2023 19:11:02 +0800 Subject: [PATCH] clean fluid elementwise_max and square api. (#2852) --- paddlespeech/s2t/training/gradclip.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/paddlespeech/s2t/training/gradclip.py b/paddlespeech/s2t/training/gradclip.py index 26ac501e..b2c0500d 100644 --- a/paddlespeech/s2t/training/gradclip.py +++ b/paddlespeech/s2t/training/gradclip.py @@ -43,7 +43,7 @@ class ClipGradByGlobalNormWithLog(paddle.nn.ClipGradByGlobalNorm): if g.type == core.VarDesc.VarType.SELECTED_ROWS: merge_grad = layers.merge_selected_rows(g) merge_grad = layers.get_tensor_from_selected_rows(merge_grad) - square = layers.square(merge_grad) + square = paddle.square(merge_grad) sum_square = layers.reduce_sum(square) sum_square_list.append(sum_square) @@ -66,7 +66,7 @@ class ClipGradByGlobalNormWithLog(paddle.nn.ClipGradByGlobalNorm): shape=[1], dtype=global_norm_var.dtype, value=self.clip_norm) clip_var = layers.elementwise_div( x=max_global_norm, - y=layers.elementwise_max(x=global_norm_var, y=max_global_norm)) + y=paddle.maximum(x=global_norm_var, y=max_global_norm)) for i, (p, g) in enumerate(params_grads): if g is None: continue -- GitLab