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@@ -84,7 +84,7 @@ class _ClipByGlobalNorm(Cell): |
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super(_ClipByGlobalNorm, self).__init__() |
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# Add interface. This parameter is not used at present |
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if use_norm is not None: |
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validator.check_number("use_norm", use_norm, 0.0, Rel.GE, self.cls_name) |
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raise ValueError("Input 'use_norm' only supports None currently!") |
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validator.check_number("clip_norm", clip_norm, 0.0, Rel.GT, self.cls_name) |
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self.clip_norm = Tensor([clip_norm], mstype.float32) |
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self.hyper_map = C.HyperMap() |
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@@ -108,16 +108,17 @@ def _check_value(clip_norm): |
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def clip_by_global_norm(x, clip_norm=1.0, use_norm=None): |
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r""" |
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Clips tensor values by the ratio of the sum of their norms. |
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Note: |
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'input x' should be a tuple or list of tensors. Otherwise, it will raise an error. |
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input 'x' should be a tuple or list of tensors. Otherwise, it will raise an error. |
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Args: |
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x (Union(tuple[Tensor], list[Tensor])): Input data to clip. |
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clip_norm (Union(float, int)): The clipping ratio. Default: 1.0 |
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clip_norm (Union(float, int)): The clipping ratio, it should be greater than 0. Default: 1.0 |
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use_norm (None): The global norm. Default: None. Currently only none is supported. |
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Returns: |
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Tensor, a clipped Tensor. |
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tuple[Tensor], a clipped Tensor. |
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Examples: |
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>>> x1 = np.array([[2., 3.],[1., 2.]]).astype(np.float32) |
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