chore: import upstream snapshot with attribution
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wehub-resource-sync
@@ -0,0 +1,39 @@
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{% from "utils.cc.j2" import static_prim_api %}
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// Generated by /paddle/fluid/prim/api/auto_code_generated/static_gen.py.
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// DO NOT EDIT!
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#include <string.h>
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#include <memory>
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#include <sstream>
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#include <string>
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#include <unordered_set>
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#include <vector>
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#include <algorithm>
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#include <tuple>
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#include "paddle/fluid/framework/block_desc.h"
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#include "paddle/fluid/framework/op_desc.h"
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#include "paddle/fluid/framework/op_proto_maker.h"
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#include "paddle/fluid/framework/operator.h"
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/framework/convert_utils.h"
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#include "paddle/fluid/prim/api/generated_prim/prim_generated_api.h"
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#include "paddle/fluid/prim/api/manual_prim/utils/utils.h"
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#include "paddle/fluid/prim/utils/static/composite_grad_desc_maker.h"
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#include "paddle/fluid/prim/utils/static/desc_tensor.h"
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#include "paddle/phi/api/include/tensor.h"
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#include "paddle/phi/common/data_type.h"
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#include "paddle/phi/common/float16.h"
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#include "paddle/phi/core/enforce.h"
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namespace paddle {
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namespace prim {
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{% for api in apis %}
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{{static_prim_api(api)}}
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{% endfor %}
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} // namespace prim
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} // namespace paddle
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@@ -0,0 +1,200 @@
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{% macro static_prim_api(api) %}
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{%- set fluid_name = api.op_name -%}
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{%- set phi_name = api.name -%}
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{%- set inputs = api.inputs -%}
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{%- set outputs = api.outputs|trip_intermediate -%} {#- ignore intermediate output -#}
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{%- set attrs = api.attrs -%}
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{%- set output_names = [] -%}
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{%- for o in outputs -%} {%- do output_names.append(o.name) -%} {%-endfor-%}
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{%- set output_dtype = static_prim_api_output_dtype(api.inputs, api.attrs) -%}
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{{static_prim_api_sig(phi_name, inputs, outputs, attrs)}} {
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framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock();
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framework::OpDesc* op = block->AppendOp();
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op->SetType("{{fluid_name}}");
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{% filter indent(2, True) %}
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{% for input in inputs %}
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{{static_prim_api_input(input)}}
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{% endfor %}
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{% for output in outputs %}
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{{static_prim_api_output(output, output_dtype)}}
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{% endfor %}
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{% for attr in attrs %}
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{{static_prim_api_attr(attr)}}
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{% endfor %}
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{% endfilter %}
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op->CheckAttrs();
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op->InferVarType(block);
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op->InferShape(*block);
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{% if outputs|length > 1 %}
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return std::make_tuple{{sequence('(', ')', ', ', output_names)}};
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{% elif outputs|length == 1 %}
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return {{outputs[0].name}};
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{% else %} {#- render nothing -#}
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{% endif %}
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}
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{% endmacro %}
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{%- macro static_prim_api_sig(name, inputs, outputs, attrs) -%}
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template <>
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{{static_prim_api_sig_ret(outputs)}} {{name}}<DescTensor>({{static_prim_api_sig_params(inputs, attrs)}})
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{%- endmacro %}
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{%- macro static_prim_api_sig_params(inputs, attrs) -%}
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{%- set input_params = [] -%}
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{%- for i in inputs -%} {%- do input_params.append(i.typename|to_paddle_input_type(i.optional)~' '~i.name) -%} {%- endfor -%}
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{%- set attr_params = [] -%}
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{%- for i in attrs -%} {%- do attr_params.append(i.typename|to_paddle_attr_type~' '~i.name) -%} {%- endfor -%}
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{{sequence('', '', ', ', input_params)}}
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{%- if attr_params|length > 0 -%} {{", "}} {%- endif -%} {#- append comma between inputs and attrs -#}
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{{sequence('', '', ', ', attr_params)}}
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{%- endmacro -%}
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{%- macro static_prim_api_sig_ret(outputs) -%}
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{%- set names = [] -%}
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{%- for i in outputs -%} {%- do names.append(i.typename|to_paddle_output_type) -%} {%- endfor -%}
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{%- if names|length > 1 -%}
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std::tuple<{{sequence('', '', ', ', names)}}>
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{%- else -%}
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{{names[0]}}
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{%- endif -%}
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{%- endmacro -%}
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{% macro static_prim_api_input(input) %}
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{%- if input.optional -%}
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{{static_prim_api_input_optional(input)}}
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{%- else -%}
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{{static_prim_api_input_without_optional(input)}}
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{%- endif -%}
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{%- endmacro -%}
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{%- macro static_prim_api_input_optional(input) -%}
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{%- if input.typename=='Tensor[]' -%} {#- render the input of type paddle::optional<std::Vector<Tensor>> -#}
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if ({{input.name}}) {
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std::vector<std::string> {{input.name}}_names({{input.name}}.get().size());
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std::transform({{input.name}}.get().begin(), {{input.name}}.get().end(), {{input.name}}_names.begin(), [](const Tensor& t) {
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return std::static_pointer_cast<prim::DescTensor>(t.impl())->Name();
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});
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op->SetInput("{{input.fluid_name | to_pascal}}", {{input.name}}_names);
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}
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{%- else -%}
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if ({{input.name}}) {
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op->SetInput("{{input.fluid_name | to_pascal}}", {std::static_pointer_cast<prim::DescTensor>({{input.name}}->impl())->Name()});
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}
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{%- endif -%}
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{%- endmacro -%}
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{%- macro static_prim_api_input_without_optional(input) -%}
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{%- if input.typename is tensor_sequence -%} {#- render the input of type std::Vector<Tensor> -#}
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std::vector<std::string> {{input.name}}_names({{input.name}}.size());;
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std::transform({{input.name}}.begin(), {{input.name}}.end(), {{input.name}}_names.begin(), [](const Tensor& t) {
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return std::static_pointer_cast<prim::DescTensor>(t.impl())->Name();
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});
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op->SetInput("{{input.fluid_name | to_pascal}}", {{input.name}}_names);
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{%- else -%}
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op->SetInput("{{input.fluid_name | to_pascal}}", {std::static_pointer_cast<prim::DescTensor>({{input.name}}.impl())->Name()});
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{%- endif -%}
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{%- endmacro -%}
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{% macro static_prim_api_output(output, dtype) %}
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{%- if output.optional -%}
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{{static_prim_api_output_optional(output, dtype)}}
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{%- else -%}
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{{static_prim_api_output_without_optional(output, dtype)}}
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{%- endif -%}
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{%- endmacro -%}
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{%- macro static_prim_api_output_without_optional(output, dtype) -%}
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{%- if output.typename is tensor_sequence -%} {#- render the output of type std::Vector<Tensor> -#}
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std::vector<Tensor> {{output.name}};
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std::vector<std::string> {{output.name}}_names;
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for (size_t i=0; i<{{output.size}}; i++) {
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auto tmp = empty<DescTensor>({}, {{dtype}}, paddle::Place());
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{{output.name}}.push_back(tmp);
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{{output.name}}_names.push_back(std::static_pointer_cast<prim::DescTensor>(tmp.impl())->Name());
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}
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op->SetOutput("{{output.fluid_name | to_pascal}}", {{output.name}}_names);
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{%- else -%}
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auto {{output.name}} = empty<DescTensor>({}, {{dtype}}, paddle::Place());
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op->SetOutput("{{output.fluid_name | to_pascal}}", {std::static_pointer_cast<prim::DescTensor>({{output.name}}.impl())->Name()});
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{%- endif -%}
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{%- endmacro -%}
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{%- macro static_prim_api_output_optional(output, dtype) -%}
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// TODO(cxxly): Render optional output
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{%- endmacro -%}
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{% macro static_prim_api_attr(attr) %}
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op->SetAttr("{{attr.fluid_name}}", {{phi_attr_to_fluid(attr)}});
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{%- endmacro %}
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{%- macro phi_attr_to_fluid(attr) -%}
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{%- if attr.typename is intarray -%}
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{{int_array_to_fluid(attr.name, attr.typename, attr.fluid_name, attr.data_type)}}
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{%- elif attr.typename is scalar -%}
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{{scalar_to_fluid(attr.name, attr.typename, attr.fluid_name, attr.data_type)}}
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{%- elif attr.typename is datatype -%}
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{{datatype_to_fluid(attr.name, attr.typename, attr.fluid_name, attr.data_type)}}
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{%- else -%}
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{{attr.name}}
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{%- endif -%}
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{%- endmacro %}
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{%- macro int_array_to_fluid(src_name, src_type, dst_name, dst_type) -%}
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{%- if dst_type=='std::vector<int>' -%}
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unsafe_vector_cast<int64_t, int>({{src_name}}.GetData())
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{%- else -%}
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{{src_name}}.GetData()
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{%- endif -%}
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{%- endmacro -%}
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{%- macro scalar_to_fluid(src_name, src_type, dst_name, dst_type) -%}
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{{src_name}}.to<{{dst_type}}>()
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{%- endmacro -%}
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{%- macro datatype_to_fluid(src_name, src_type, dst_name, dst_type) -%}
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paddle::framework::TransToProtoVarType({{src_name}})
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{%- endmacro -%}
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{%- macro sequence(lsymbol, rsymbol, delimiter, items) -%}
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{{lsymbol}}{%- for item in items -%}{{item}}{{delimiter if not loop.last else "" }}{%- endfor -%}{{rsymbol}}
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{%- endmacro -%}
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{%- macro static_prim_api_output_dtype(inputs, attrs) -%}
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{%- set is_set = [] -%} {#- why not use boolean, ref: https://stackoverflow.com/questions/17925674/jinja2-local-global-variable -#}
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{%- if not is_set -%} {#- use DataType attr as default output dtype -#}
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{%- for attr in attrs -%}
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{%- if attr.typename is datatype -%}
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{{attr.name}}
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{%- do is_set.append(1) -%}
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{%- endif -%}
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{%- endfor -%}
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{%- endif -%}
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{%- if not is_set -%} {#- use first input named x dtype as default output dtype -#}
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{%- for input in inputs -%}
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{%- if input.typename == 'Tensor' and input.name == 'x' -%}
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{{input.name}}.dtype()
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{%- do is_set.append(1) -%}
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{%- endif -%}
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{%- endfor -%}
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{%- endif -%}
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{%- if not is_set -%} {#- use fp32 as default output dtype -#}
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phi::DataType::FLOAT32
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{%- endif -%}
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{%- endmacro -%}
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