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Fixed SparseReorder bprop with graph mode

This commit is contained in:
BokaiLi 2023-02-25 17:48:57 +08:00
parent e5e8d7bb10
commit d7ad67b715
1 changed files with 2 additions and 2 deletions
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4
mindspore/python/mindspore/ops/_grad_experimental/grad_sparse_ops.py
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@ -133,7 +133,7 @@ def get_bprop_sparse_softmax(self):
default_values = _create_tensor(0, values.dtype)
out_dout = mul(out, dout)
sp_product = sparse_to_dense(indices, shape, out_dout, default_values)
sum_reduced = -reduce_sum(sp_product, -1)
sum_reduced = -1 * reduce_sum(sp_product, -1)
sp_sum = sparse_dense_cwise_add(indices, dout, shape, sum_reduced)
grad_x = mul(sp_sum, out)
return zeros_like(indices), grad_x, zeros_like(shape)
@ -387,7 +387,7 @@ def get_bprop_sparse_reorder(self):
def bprop(indices, values, shape, out, dout):
num_entries = F.shape(indices)[0]
start = Tensor(0, dtype=mstype.int32)
limit = Tensor(num_entries, dtype=mstype.int32)
limit = P.Cast()(num_entries, mstype.int32)
delta = Tensor(1, dtype=mstype.int32)
entry_indices = range_op(start, limit, delta)
output = sparse_reorder_op(indices, entry_indices, shape)