forked from OSSInnovation/mindspore
eager mode enable sparse
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@ -150,7 +150,8 @@ PrimitiveEvalImplMap &GetPrimitiveToEvalImplMap() {
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using mindspore::parse::PyObjectWrapper;
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EvalResultPtr StandardPrimEvaluator::EvalPrim(const AnalysisEnginePtr &engine, const AbstractBasePtrList &args) {
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if (prim_ != prim::kPrimMakeTuple && prim_ != prim::kPrimSwitch) {
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if (prim_ != prim::kPrimMakeTuple && prim_ != prim::kPrimSwitch && prim_ != prim::kPrimEnvSetItem &&
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prim_ != prim::kPrimEnvGetItem) {
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auto ret_abstract = AbstractEval(args);
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if (ret_abstract != nullptr) {
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MS_LOG(DEBUG) << "StandardPrimEvaluator eval Undetermined";
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@ -217,17 +217,20 @@ class IndexedSlices:
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A sparse representation of a set of tensor slices at given indices.
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An IndexedSlices is typically used to represent a subset of a larger
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tensor dense of shape [LARGE0, D1, .. , DN] where LARGE0 >> D0.
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tensor dense of shape [L0, D1, .. , DN] where L0 >> D0.
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The values in indices are the indices in the first dimension of the slices
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that have been extracted from the larger tensor.
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that have been extracted from the larger tensor.
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The dense tensor dense represented by an IndexedSlices slices has
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`dense[slices.indices[i], :, :, :, ...] = slices.values[i, :, :, :, ...]`.
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`dense[slices.indices[i], :, :, :, ...] = slices.values[i, :, :, :, ...]`.
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IndexedSlices can only be used in `Cell`'s contruct method.
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Args:
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indices (Tensor): A 1-D integer Tensor of shape [D0].
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values (Tensor): A Tensor of any dtype of shape [D0, D1, ..., Dn].
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dense_shape: (tuple): A integer tuple containing the shape
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dense_shape (tuple): A integer tuple containing the shape
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of the corresponding dense tensor.
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Returns:
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@ -254,8 +257,9 @@ class SparseTensor:
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A sparse representation of a set of nonzero elememts from a tensor at given indices.
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SparseTensor can only be used in `Cell`'s contruct method.
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For a tensor dense, its SparseTensor(indices, values, dense_shape) has
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`dense[indices[i]] = values[i]`.
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`dense[indices[i]] = values[i]`.
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Args:
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indices (Tensor): A 2-D integer Tensor of shape `[N, ndims]`,
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@ -263,7 +267,7 @@ class SparseTensor:
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the SparseTensor, respectively.
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values (Tensor): A 1-D tensor of any type and shape `[N]`, which
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supplies the values for each element in indices.
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dense_shape: (tuple): A integer tuple of size `ndims`,
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dense_shape (tuple): A integer tuple of size `ndims`,
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which specifies the dense_shape of the sparse tensor.
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Returns:
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