update hel

docs/api/api_python/nn/mindspore.nn.HingeEmbeddingLoss.rst

@@ -35,8 +35,8 @@ mindspore.nn.HingeEmbeddingLoss
         Tensor或Tensor scalar，根据 :math:`reduction` 计算的loss。
 
     异常：
-        - **TypeError** - `logits` 不是数据类型为float的Tensor。
-        - **TypeError** - `labels` 不是数据类型为float的Tensor。
+        - **TypeError** - `logits` 不是Tensor。
+        - **TypeError** - `labels` 不是Tensor。
         - **TypeError** - `margin` 不是float或int。
-        - **ValueError** - `labels` 和 `logits` shape不一致。
+        - **ValueError** - `labels` 和 `logits` shape不一致且不能广播。
         - **ValueError** - `reduction` 不是"none"、"mean"或者"sum"。

docs/api/api_python/ops/mindspore.ops.func_hinge_embedding_loss.rst

@@ -33,8 +33,8 @@ mindspore.ops.hinge_embedding_loss
         Tensor或Tensor scalar，根据 :math:`reduction` 计算的loss。
 
     异常：
-        - **TypeError** - `inputs` 不是数据类型为float的Tensor。
-        - **TypeError** - `targets` 不是数据类型为float的Tensor。
+        - **TypeError** - `inputs` 不是Tensor。
+        - **TypeError** - `targets` 不是Tensor。
         - **TypeError** - `margin` 不是float或者int。
-        - **ValueError** - `inputs` 和 `targets` shape不一致。
+        - **ValueError** - `inputs` 和 `targets` shape不一致且不能广播。
         - **ValueError** - `reduction` 不是"none"、"mean"或者"sum"。

mindspore/python/mindspore/nn/loss/loss.py

@@ -2505,10 +2505,10 @@ class HingeEmbeddingLoss(LossBase):
         Tensor or Tensor scalar, the computed loss depending on `reduction`.
 
     Raises:
-        TypeError: If `logits` is not a Tensor of floats.
-        TypeError: If `labels` is not a Tensor of floats.
+        TypeError: If `logits` is not a Tensor.
+        TypeError: If `labels` is not a Tensor.
         TypeError: If `margin` is not a float or int.
-        ValueError: If `labels` does not have the same shape as `logits`.
+        ValueError: If `labels` does not have or could not broadcast to the same shape as `logits`.
         ValueError: If `reduction` is not one of 'none', 'mean', 'sum'.
 
     Supported Platforms:

mindspore/python/mindspore/ops/function/nn_func.py

@@ -4099,10 +4099,10 @@ def hinge_embedding_loss(inputs, targets, margin=1.0, reduction='mean'):
         Tensor or Tensor scalar, the computed loss depending on `reduction`.
 
     Raises:
-        TypeError: If `inputs` is not a Tensor of floats.
-        TypeError: If `targets` is not a Tensor of floats.
+        TypeError: If `inputs` is not a Tensor.
+        TypeError: If `targets` is not a Tensor.
         TypeError: If `margin` is not a float or int.
-        ValueError: If `targets` does not have the same shape as `inputs`.
+        ValueError: If `targets` does not have or could not broadcast to the same shape as `inputs`.
         ValueError: If `reduction` is not one of 'none', 'mean', 'sum'.
 
     Supported Platforms:
@@ -4126,14 +4126,11 @@ def hinge_embedding_loss(inputs, targets, margin=1.0, reduction='mean'):
     if reduction not in ['none', 'mean', 'sum']:
         raise ValueError(f"For 'HingeEmbeddingLoss', 'reduction' must be one of 'none', 'mean', 'sum',"
                          f"but got {reduction}.")
+    if not isinstance(inputs, Tensor):
+        raise TypeError(f"For 'HingeEmbeddingLoss', the first input must be a Tensor, but got {type(inputs)}.")
+    if not isinstance(targets, Tensor):
+        raise TypeError(f"For 'HingeEmbeddingLoss', the second input must be a Tensor, but got {type(targets)}.")
     inputs_dtype = inputs.dtype
-    targets_dtype = targets.dtype
-    if inputs_dtype not in mstype.float_type:
-        raise TypeError(f"For 'HingeEmbeddingLoss', the dtype of the first input must be float, but got "
-                        f"{inputs_dtype}.")
-    if targets_dtype not in mstype.float_type:
-        raise TypeError(f"For 'HingeEmbeddingLoss', the dtype of the second input must be float, but got "
-                        f"{targets_dtype}.")
     min_val = Tensor(0, inputs_dtype)
     pos_index = targets > 0
     neg_index = targets < 0