add pack bprop

mindspore/ops/_grad/grad_array_ops.py

@@ -386,38 +386,6 @@ def _regenerate_output_shape(x_shp, ind_shp, axis):
 
 
 @bprop_getters.register(P.Gather)
-def get_bprop_gather(self):
-    """Generate bprop for GatherV2"""
-
-    def bprop(x, indices, axis, out, dout):
-        orig_indices = indices
-        if F.rank(dout) == 0:
-            dout = P.ExpandDims()(dout, -1)
-        if F.rank(indices) == 0:
-            indices = P.ExpandDims()(indices, -1)
-            x_shp = shape_op(x)
-            ind_shp = shape_op(indices)
-            out_shp = _regenerate_output_shape(x_shp, ind_shp, axis)
-            dout = reshape(dout, out_shp)
-
-        x_shp = shape_op(x)
-        out_shp = shape_op(dout)
-        ind_shp = shape_op(indices)
-        # Example: out_shape:(3,2,3) axis 1 -> (1,0,2)
-        perm_1 = _generate_shape_index(out_shp, ind_shp, axis)
-        values_transpose = transpose(dout, perm_1)
-        if -1 in shape_op(x):
-            params_grad = unsorted_segment_sum(values_transpose, indices, dyn_shape_op(x)[axis])
-        else:
-            params_grad = unsorted_segment_sum(values_transpose, indices, shape_op(x)[axis])
-        # Example: out_shape:(3,2,3) axis 2 -> (1,2,0)
-        perm_2 = _generate_inverse_index(x_shp, axis)
-        params_grad = transpose(params_grad, perm_2)
-        return params_grad, zeros_like(orig_indices), zeros_like(axis)
-
-    return bprop
-
-
 @bprop_getters.register(P.GatherV2)
 def get_bprop_gather_v2(self):
     """Generate bprop for GatherV2"""
@@ -601,6 +569,7 @@ def get_bprop_range(self):
     return bprop
 
 
+@bprop_getters.register(P.Pack)
 @bprop_getters.register(P.Stack)
 def get_bprop_stack(self):
     """Generate bprop for Stack"""