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Test link error
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5173d1c721
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5 changed files with 15 additions and 4 deletions
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@ -6,6 +6,9 @@
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namespace onnxruntime {
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namespace contrib {
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void LinkerTest() {
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}
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Status LongformerAttentionBase::CheckInputs(const TensorShape& input_shape,
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const TensorShape& weights_shape,
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const TensorShape& bias_shape,
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@ -9,6 +9,8 @@
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namespace onnxruntime {
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namespace contrib {
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void LinkerTest();
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class LongformerAttentionBase {
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public:
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Status CheckInputs(const TensorShape& input_shape,
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@ -826,7 +826,10 @@ struct ProviderHostImpl : ProviderHost {
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#ifndef DISABLE_CONTRIB_OPS
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Status embed_layer_norm__CheckInputs(const OpKernelContext* context) override { return contrib::embed_layer_norm::CheckInputs(context); }
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Status bias_gelu_helper__CheckInputs(const OpKernelContext* context) override { return contrib::bias_gelu_helper::CheckInputs(context); }
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Status LongformerAttentionBase__CheckInputs(const contrib::LongformerAttentionBase* p, const TensorShape& input_shape, const TensorShape& weights_shape, const TensorShape& bias_shape, const TensorShape& mask_shape, const TensorShape& global_weights_shape, const TensorShape& global_bias_shape, const TensorShape& global_shape) override { return p->CheckInputs(input_shape, weights_shape, bias_shape, mask_shape, global_weights_shape, global_bias_shape, global_shape); }
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Status LongformerAttentionBase__CheckInputs(const contrib::LongformerAttentionBase* p, const TensorShape& input_shape, const TensorShape& weights_shape, const TensorShape& bias_shape, const TensorShape& mask_shape, const TensorShape& global_weights_shape, const TensorShape& global_bias_shape, const TensorShape& global_shape) override {
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contrib::LinkerTest();
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return p->CheckInputs(input_shape, weights_shape, bias_shape, mask_shape, global_weights_shape, global_bias_shape, global_shape);
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}
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Status AttentionBase__CheckInputs(const contrib::AttentionBase* p, const TensorShape& input_shape, const TensorShape& weights_shape, const TensorShape& bias_shape, const Tensor*& mask_index, const Tensor* past, const int max_threads_per_block) override { return p->CheckInputs(input_shape, weights_shape, bias_shape, mask_index, past, max_threads_per_block); }
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Tensor* AttentionBase__GetPresent(const contrib::AttentionBase* p, OpKernelContext* context, const Tensor* past, int batch_size, int head_size, int sequence_length, int& past_sequence_length) override { return p->GetPresent(context, past, batch_size, head_size, sequence_length, past_sequence_length); }
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#endif
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@ -840,7 +843,7 @@ struct ProviderHostImpl : ProviderHost {
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void contrib__GetNDCFromLogitAndLabelShape(const TensorShape& logit_shape, const TensorShape& label_shape, int64_t& N_D, int64_t& C) override { contrib::GetNDCFromLogitAndLabelShape(logit_shape, label_shape, N_D, C); }
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void contrib__GetPermutationAndShape(bool ncd_to_ndc, const TensorShape& tensor_shape, std::vector<int64_t>& new_shape, std::vector<size_t>& permutations) override { contrib::GetPermutationAndShape(ncd_to_ndc, tensor_shape, new_shape, permutations); }
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Status contrib__PrepareForTrainingCompute(const TensorShape& input_shape, int num_outputs, int64_t& axis, int& before_dims, int& after_dims_including_split_axis, int& after_dims_excluding_split, std::vector<int64_t>& split_sizes) override { return contrib::PrepareForTrainingCompute(input_shape, num_outputs, axis, before_dims, after_dims_including_split_axis, after_dims_excluding_split, split_sizes); }
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Status YieldOp__Compute(const contrib::YieldOp* p, OpKernelContext* context) override { return p->Compute(context); }
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Status contrib__YieldOp__Compute(const contrib::YieldOp* p, OpKernelContext* context) override { return p->Compute(context); }
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#endif
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#endif
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} provider_host_;
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@ -436,8 +436,11 @@ PhiloxGenerator& PhiloxGenerator::Default() { return g_host->PhiloxGenerator__De
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Status Einsum::Compute(OpKernelContext* context) const { return g_host->Einsum__Compute(this, context); }
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template <>
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std::unique_ptr<EinsumTypedComputeProcessor<float>> EinsumTypedComputeProcessor<float>::Create(OpKernelContext* context, AllocatorPtr allocator, concurrency::ThreadPool* tp, EinsumComputePreprocessor& einsum_compute_preprocessor, void* einsum_cuda_assets) { return g_host->EinsumTypedComputeProcessor_float__Create(context, allocator, tp, einsum_compute_preprocessor, einsum_cuda_assets); }
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template <>
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std::unique_ptr<EinsumTypedComputeProcessor<double>> EinsumTypedComputeProcessor<double>::Create(OpKernelContext* context, AllocatorPtr allocator, concurrency::ThreadPool* tp, EinsumComputePreprocessor& einsum_compute_preprocessor, void* einsum_cuda_assets) { return g_host->EinsumTypedComputeProcessor_double__Create(context, allocator, tp, einsum_compute_preprocessor, einsum_cuda_assets); }
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template <>
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std::unique_ptr<EinsumTypedComputeProcessor<MLFloat16>> EinsumTypedComputeProcessor<MLFloat16>::Create(OpKernelContext* context, AllocatorPtr allocator, concurrency::ThreadPool* tp, EinsumComputePreprocessor& einsum_compute_preprocessor, void* einsum_cuda_assets) { return g_host->EinsumTypedComputeProcessor_MLFloat16__Create(context, allocator, tp, einsum_compute_preprocessor, einsum_cuda_assets); }
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#ifndef DISABLE_CONTRIB_OPS
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@ -466,7 +469,7 @@ std::unique_ptr<OpKernel> Loop::Create(const OpKernelInfo& info, const Loop::Con
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namespace contrib {
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Status Group::Compute(OpKernelContext* context) const { return g_host->contrib__Group__Compute(this, context); }
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Status PassThrough::Compute(OpKernelContext* context) const { return g_host->contrib__PassThrough__Compute(this, context); }
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Status YieldOp::Compute(OpKernelContext* context) const { return g_host->YieldOp__Compute(this, context); }
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Status YieldOp::Compute(OpKernelContext* context) const { return g_host->contrib__YieldOp__Compute(this, context); }
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} // namespace contrib
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#endif
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#endif
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@ -756,7 +756,7 @@ struct ProviderHost {
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virtual void contrib__GetNDCFromLogitAndLabelShape(const TensorShape& logit_shape, const TensorShape& label_shape, int64_t& N_D, int64_t& C) = 0;
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virtual void contrib__GetPermutationAndShape(bool ncd_to_ndc, const TensorShape& tensor_shape, std::vector<int64_t>& new_shape, std::vector<size_t>& permutations) = 0;
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virtual Status contrib__PrepareForTrainingCompute(const TensorShape& input_shape, int num_outputs, int64_t& axis, int& before_dims, int& after_dims_including_split_axis, int& after_dims_excluding_split, std::vector<int64_t>& split_sizes) = 0;
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virtual Status YieldOp__Compute(const contrib::YieldOp* p, OpKernelContext* context) = 0;
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virtual Status contrib__YieldOp__Compute(const contrib::YieldOp* p, OpKernelContext* context) = 0;
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#endif
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#endif
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};
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