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Method Compute

en_ops/emb_convert.cc:115–141  ·  view source on GitHub ↗

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113 OP_REQUIRES(context, lib != NULL, errors::Unknown("Unable to load sgx.so!"));
114 }
115 void Compute(OpKernelContext *context) override
116 {
117
118 // get the input tensor
119 const Tensor &input = context->input(0);
120 auto input_flat = input.flat<float>();
121 // check shapes of input
122 const TensorShape &input_shape = input.shape();
123 TensorShape output_shape;
124 output_shape.AddDim(input_shape.dim_size(0) / times_);
125 output_shape.AddDim(num_ * (1 + dim_));
126 // create output tensor
127 Tensor *output = NULL;
128 OP_REQUIRES_OK(context, context->allocate_output(0, output_shape, &output));
129 auto output_flat = output->flat<float>();
130 int M = input_shape.dim_size(0) / times_;
131 int C = num_ * (1 + dim_);
132 unsigned long int eid_ = (eid_high_ << 32) + eid_low_;
133 typedef void (*function)(unsigned long int eid, float *x, float *y, int M, int C, int num, int dim);
134
135 dlerror();
136 function embedding_ss_grad_kernel = (function)dlsym(lib, "embedding_ss_grad");
137 const char *dlsym_error = dlerror();
138 OP_REQUIRES(context, !dlsym_error, errors::Unknown("loading of embedding_ss_grad failed: ", dlsym_error));
139
140 embedding_ss_grad_kernel(eid_, (float *)input_flat.data(), (float *)output_flat.data(), M, C, num_, dim_);
141 };
142
143private:
144 void *lib;

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