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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,94 @@ | ||
| // Copyright (c) Microsoft Corporation. | ||
| // Licensed under the MIT license. | ||
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| #include "logging.h" | ||
| #include "model.h" | ||
| #include <cassert> | ||
|
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| namespace ark { | ||
|
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| extern const OpConfigMap EmbeddingConfigMap; | ||
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| EmbeddingOp::EmbeddingOp(OpPrecType prec_type, Tensor *input, Tensor *weight, | ||
| Tensor *output, const std::string &name) | ||
| : Op{OP_EMBEDDING, prec_type, {input, weight}, {output}, | ||
| {}, name, &EmbeddingConfigMap, -1, | ||
| true} | ||
| { | ||
| } | ||
|
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| std::string EmbeddingOp::function_name(const OpConfig &cfg) const | ||
| { | ||
| Tensor *input = this->inputs[0]; | ||
| Tensor *weight = this->inputs[1]; | ||
| Tensor *output = this->outputs[0]; | ||
|
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| auto in_dims = input->ldims.dims4(); | ||
| auto in_shape = input->shape.dims4(); | ||
|
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| assert(in_dims[0] == 1); | ||
| assert(in_shape[0] == 1); | ||
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| Dims new_in_dims{in_dims[1], in_dims[2], in_dims[3], 1}; | ||
| Dims new_in_shape{in_shape[1], in_shape[2], in_shape[3], 1}; | ||
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| int emb_dim = weight->shape[-1]; | ||
| return Op::function_name("ark::embedding", | ||
| {{ | ||
| new_in_dims, // InDims | ||
| new_in_shape, // InShape | ||
| weight->ldims.dims4(), // WeightDims | ||
| weight->shape.dims4(), // WeightShape | ||
| output->ldims.dims4(), // OutDims | ||
| output->shape.dims4(), // OutShape | ||
| emb_dim, // EmbeddingDim | ||
| cfg.num_warps * 32, // NumThreads | ||
| }}); | ||
| } | ||
|
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| Tensor *Model::embedding(Tensor *input, Tensor *weight, Tensor *output, | ||
| const std::string &name) | ||
| { | ||
| assert(input != nullptr); | ||
| assert(weight != nullptr); | ||
| if (input->shape.ndims() > 3) { | ||
| LOG(ERROR, "input shape ndims > 3: ", input->shape); | ||
| } | ||
| if (weight->shape.ndims() != 2) { | ||
| LOG(ERROR, "weight shape ndims != 2: ", weight->shape); | ||
| } | ||
| OpPrecType pt = OP_PREC_NONE; | ||
| if (weight->type == FP16) { | ||
| pt = OP_PREC_FP16; | ||
| } else if (weight->type == FP32) { | ||
| pt = OP_PREC_FP32; | ||
| } else { | ||
| LOG(ERROR, "unsupported weight data type: ", weight->type); | ||
| } | ||
| auto emb_dim = weight->shape[-1]; | ||
|
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| std::vector<DimType> output_dims; | ||
| for (int i = 0; i < input->shape.ndims(); ++i) { | ||
| output_dims.push_back(input->shape[i]); | ||
| } | ||
| output_dims.push_back(emb_dim); | ||
| Dims out_shape{output_dims}; | ||
| if (output == nullptr) { | ||
| output = this->tensor(out_shape, weight->type); | ||
| } | ||
| EmbeddingOp op{pt, input, weight, output, name}; | ||
| return this->impl->add_op(op)[0]; | ||
| } | ||
|
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| const OpConfigMap EmbeddingConfigMap = { | ||
| {{OP_ARCH_CUDA_ANY, OP_PREC_ANY}, | ||
| { | ||
| // NumWarps, SmemBytes, InDepsTiles, OutDepsTiles, SyncPre, SyncPost | ||
| {1, 0, {{1, 1}, {1, -1}}, {{1, -1}}, true, false}, | ||
| {2, 0, {{1, 1}, {1, -1}}, {{1, -1}}, true, false}, | ||
| {4, 0, {{1, 1}, {1, -1}}, {{1, -1}}, true, false}, | ||
| {8, 0, {{1, 1}, {1, -1}}, {{1, -1}}, true, false}, | ||
| }}, | ||
| }; | ||
|
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| } // namespace ark |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,89 @@ | ||
| // Copyright (c) Microsoft Corporation. | ||
| // Licensed under the MIT license. | ||
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| #include "include/ark.h" | ||
| #include "include/ark_utils.h" | ||
| #include "ops_test_common.h" | ||
| #include "unittest/unittest_utils.h" | ||
| #include <cassert> | ||
| #include <type_traits> | ||
|
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| template <typename T> | ||
| void baseline_embedding(std::vector<void *> &outputs, | ||
| const std::vector<ark::Dims> &output_shapes, | ||
| const std::vector<void *> &inputs, | ||
| const std::vector<ark::Dims> &input_shapes) | ||
| { | ||
| T *out = static_cast<T *>(outputs[0]); | ||
| int *in = static_cast<int *>(inputs[0]); | ||
| T *weight = static_cast<T *>(inputs[1]); | ||
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| ark::Dims osh = output_shapes[0].dims4(); | ||
| ark::Dims wsh = input_shapes[1].dims4(); | ||
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| assert(osh[3] == wsh[3]); | ||
|
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| int in_idx = 0; | ||
| for (ark::DimType n = 0; n < osh[0]; ++n) { | ||
| for (ark::DimType c = 0; c < osh[1]; ++c) { | ||
| for (ark::DimType h = 0; h < osh[2]; ++h) { | ||
| int weight_idx = in[in_idx++]; | ||
| T *ptr = &weight[weight_idx * wsh[3]]; | ||
| for (ark::DimType w = 0; w < osh[3]; ++w) { | ||
| out[n * osh[1] * osh[2] * osh[3] + c * osh[2] * osh[3] + | ||
| h * osh[3] + w] = ptr[w]; | ||
| } | ||
| } | ||
| } | ||
| } | ||
| }; | ||
|
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| template <typename T> ark::unittest::State test_embedding() | ||
| { | ||
| const int num_emb = 1000; | ||
| const int emb_dim = 8192; | ||
|
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| ark::TensorType weight_type; | ||
| if (std::is_same<T, float>::value) { | ||
| weight_type = ark::FP32; | ||
| } else { | ||
| weight_type = ark::FP16; | ||
| } | ||
|
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| ark::Model m; | ||
| ark::Tensor *ti = m.tensor(ark::Dims(8, 3, 64), ark::INT32); | ||
| ark::Tensor *tw = m.tensor(ark::Dims(num_emb, emb_dim), weight_type); | ||
| ark::Tensor *to = m.embedding(ti, tw); | ||
|
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| ark::srand(); | ||
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| std::vector<int> ti_data; | ||
| for (auto i = 0; i < ti->shape.size(); ++i) { | ||
| // Random indices in [0, num_emb) | ||
| ti_data.push_back(ark::rand() % num_emb); | ||
| } | ||
| auto tw_data = ark::utils::rand_array<T>(tw->shape.size(), 1.0); | ||
| auto result = | ||
| ark::op_test("embedding_fp32", m, {ti, tw}, {to}, baseline_embedding<T>, | ||
| {ti_data.data(), tw_data.get()}); | ||
| ark::op_test_log(result); | ||
| return ark::unittest::SUCCESS; | ||
| } | ||
|
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| ark::unittest::State test_embedding_fp32() | ||
| { | ||
| return test_embedding<float>(); | ||
| } | ||
|
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| ark::unittest::State test_embedding_fp16() | ||
| { | ||
| return test_embedding<ark::half_t>(); | ||
| } | ||
|
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| int main() | ||
| { | ||
| ark::init(); | ||
| UNITTEST(test_embedding_fp32); | ||
| UNITTEST(test_embedding_fp16); | ||
| return ark::unittest::SUCCESS; | ||
| } |
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