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Commit 85d789f7 authored by Khalique's avatar Khalique
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manual merge and biasadd change

parents 864fafb2 a5b0afa0
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Showing with 3571 additions and 23 deletions
src/targets/cpu/lowering.cpp
View file @ 85d789f7
...@@ -103,6 +103,43 @@ struct cpu_batch_norm_inference ...@@ -103,6 +103,43 @@ struct cpu_batch_norm_inference
} }
}; };
struct cpu_lrn
{
op::lrn op;
std::string name() const { return "cpu::lrn"; }
shape compute_shape(const std::vector<shape>& inputs) const { return op.compute_shape(inputs); }
argument compute(context&, shape output_shape, std::vector<argument> args) const
{
argument result{output_shape};
visit_all(result, args[0])([&](auto output, auto input) {
int n_batch = output_shape.lens()[0];
int channels = output_shape.lens()[1];
int height = output_shape.lens()[2];
int width = output_shape.lens()[3];
float alphaoverarea = op.alpha / op.size;
int radius = (op.size - 1) / 2;
par_dfor(n_batch, height, width)([&](int b, int h, int w) {
float scale = 0;
dfor(channels)([&](int c) {
auto start = (c - radius) < 0 ? 0 : (c - radius);
auto end = (c + radius) > channels ? channels : (c + radius);
for(auto k = start; k < end; ++k)
{
scale += std::pow(input(b, k, h, w), 2);
}
scale *= alphaoverarea;
scale += op.bias;
scale = std::pow(scale, -op.beta);
output(b, c, h, w) = input(b, c, h, w) * scale;
});
});
});
return result;
}
};
struct cpu_convolution struct cpu_convolution
{ {
op::convolution op; op::convolution op;
...@@ -287,14 +324,7 @@ struct cpu_contiguous ...@@ -287,14 +324,7 @@ struct cpu_contiguous
shape compute_shape(const std::vector<shape>& inputs) const { return op.compute_shape(inputs); } shape compute_shape(const std::vector<shape>& inputs) const { return op.compute_shape(inputs); }
argument compute(context&, const shape& output_shape, std::vector<argument> args) const argument compute(context&, const shape& output_shape, std::vector<argument> args) const
{ {
assert(output_shape.standard()); return op.compute(output_shape, std::move(args));
argument result{output_shape};
visit_all(result, args[0])([&](auto output, auto input) {
shape_for_each(output.get_shape(), [&](const auto& idx) {
output(idx.begin(), idx.end()) = input(idx.begin(), idx.end());
});
});
return result;
} }
}; };
...@@ -688,6 +718,7 @@ struct cpu_apply ...@@ -688,6 +718,7 @@ struct cpu_apply
apply_map["dot"] = extend_op<cpu_gemm, op::dot>(); apply_map["dot"] = extend_op<cpu_gemm, op::dot>();
apply_map["batch_norm_inference"] = apply_map["batch_norm_inference"] =
extend_op<cpu_batch_norm_inference, op::batch_norm_inference>(); extend_op<cpu_batch_norm_inference, op::batch_norm_inference>();
apply_map["lrn"] = extend_op<cpu_lrn, op::lrn>();
apply_map["contiguous"] = extend_op<cpu_contiguous, op::contiguous>(); apply_map["contiguous"] = extend_op<cpu_contiguous, op::contiguous>();
apply_map["pad"] = extend_op<cpu_pad, op::pad>(); apply_map["pad"] = extend_op<cpu_pad, op::pad>();
apply_map["concat"] = extend_op<cpu_concat, op::concat>(); apply_map["concat"] = extend_op<cpu_concat, op::concat>();
......
src/targets/cpu/target.cpp
View file @ 85d789f7
...@@ -2,6 +2,8 @@ ...@@ -2,6 +2,8 @@
#include <migraphx/cpu/target.hpp> #include <migraphx/cpu/target.hpp>
#include <migraphx/cpu/lowering.hpp> #include <migraphx/cpu/lowering.hpp>
#include <migraphx/auto_contiguous.hpp> #include <migraphx/auto_contiguous.hpp>
#include <migraphx/rewrite_rnn.hpp>
#include <migraphx/dead_code_elimination.hpp>
namespace migraphx { namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS { inline namespace MIGRAPHX_INLINE_NS {
...@@ -11,7 +13,11 @@ std::string target::name() const { return "cpu"; } ...@@ -11,7 +13,11 @@ std::string target::name() const { return "cpu"; }
std::vector<pass> target::get_passes(migraphx::context&) const std::vector<pass> target::get_passes(migraphx::context&) const
{ {
return {auto_contiguous{}, lowering{}}; return {auto_contiguous{},
rewrite_rnn{},
dead_code_elimination{},
lowering{},
dead_code_elimination{}};
} }
} // namespace cpu } // namespace cpu
......
src/targets/gpu/CMakeLists.txt
View file @ 85d789f7
...@@ -30,6 +30,7 @@ add_library(migraphx_device ...@@ -30,6 +30,7 @@ add_library(migraphx_device
device/concat.cpp device/concat.cpp
device/pad.cpp device/pad.cpp
device/gather.cpp device/gather.cpp
device/sub.cpp
) )
set_target_properties(migraphx_device PROPERTIES EXPORT_NAME device) set_target_properties(migraphx_device PROPERTIES EXPORT_NAME device)
rocm_clang_tidy_check(migraphx_device) rocm_clang_tidy_check(migraphx_device)
...@@ -60,6 +61,7 @@ add_library(migraphx_gpu ...@@ -60,6 +61,7 @@ add_library(migraphx_gpu
elu.cpp elu.cpp
pad.cpp pad.cpp
gather.cpp gather.cpp
lrn.cpp
) )
set_target_properties(migraphx_gpu PROPERTIES EXPORT_NAME gpu) set_target_properties(migraphx_gpu PROPERTIES EXPORT_NAME gpu)
rocm_clang_tidy_check(migraphx_gpu) rocm_clang_tidy_check(migraphx_gpu)
......
src/targets/gpu/device/sub.cpp 0 → 100644
View file @ 85d789f7
#include <migraphx/gpu/device/sub.hpp>
#include <migraphx/gpu/device/nary.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
namespace device {
void sub(hipStream_t stream, const argument& result, const argument& arg1, const argument& arg2)
{
nary(stream, result, arg1, arg2)([](auto x, auto y) { return y - x; });
}
} // namespace device
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
src/targets/gpu/gemm.cpp
View file @ 85d789f7
...@@ -107,6 +107,7 @@ argument miopen_gemm::compute(context& ctx, ...@@ -107,6 +107,7 @@ argument miopen_gemm::compute(context& ctx,
ldc); ldc);
}); });
return args[2]; return args[2];
} }
......
src/targets/gpu/include/migraphx/gpu/device/sub.hpp 0 → 100644
View file @ 85d789f7
#ifndef MIGRAPHX_GUARD_RTGLIB_DEVICE_SUB_HPP
#define MIGRAPHX_GUARD_RTGLIB_DEVICE_SUB_HPP
#include <migraphx/argument.hpp>
#include <migraphx/config.hpp>
#include <hip/hip_runtime_api.h>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
namespace device {
void sub(hipStream_t stream, const argument& result, const argument& arg1, const argument& arg2);
} // namespace device
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif
src/targets/gpu/include/migraphx/gpu/lrn.hpp 0 → 100644
View file @ 85d789f7
#ifndef MIGRAPHX_GUARD_RTGLIB_LRN_HPP
#define MIGRAPHX_GUARD_RTGLIB_LRN_HPP
#include <migraphx/gpu/lowering.hpp>
#include <migraphx/manage_ptr.hpp>
#include <migraphx/instruction.hpp>
#include <migraphx/operators.hpp>
#include <migraphx/generate.hpp>
#include <migraphx/shape_for_each.hpp>
#include <migraphx/config.hpp>
#include <migraphx/gpu/miopen.hpp>
#include <migraphx/gpu/hip.hpp>
#include <migraphx/dfor.hpp>
#include <migraphx/gpu/device/contiguous.hpp>
#include <migraphx/gpu/device/add.hpp>
#include <migraphx/iterator_for.hpp>
#include <migraphx/gpu/rocblas.hpp>
#include <migraphx/gpu/context.hpp>
#include <utility>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
struct miopen_lrn
{
shared<lrn_descriptor> ldesc;
std::string name() const { return "gpu::lrn"; }
shape compute_shape(const std::vector<shape>& inputs) const;
argument
compute(context& ctx, const shape& output_shape, const std::vector<argument>& args) const;
int output_alias(const std::vector<shape>& shapes) const { return shapes.size() - 1; }
};
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif
src/targets/gpu/include/migraphx/gpu/miopen.hpp
View file @ 85d789f7
...@@ -23,6 +23,8 @@ using fusion_plan_descriptor = MIGRAPHX_MANAGE_PTR(miopenFusionPlanDescriptor_t, ...@@ -23,6 +23,8 @@ using fusion_plan_descriptor = MIGRAPHX_MANAGE_PTR(miopenFusionPlanDescriptor_t,
miopenDestroyFusionPlan); miopenDestroyFusionPlan);
using fused_operator_args = MIGRAPHX_MANAGE_PTR(miopenOperatorArgs_t, miopenDestroyOperatorArgs); using fused_operator_args = MIGRAPHX_MANAGE_PTR(miopenOperatorArgs_t, miopenDestroyOperatorArgs);
using lrn_descriptor = MIGRAPHX_MANAGE_PTR(miopenLRNDescriptor_t, miopenDestroyLRNDescriptor);
template <class Result, class F, class... Ts> template <class Result, class F, class... Ts>
Result make_obj(F f, Ts... xs) Result make_obj(F f, Ts... xs)
{ {
...@@ -89,6 +91,13 @@ inline pooling_descriptor make_pooling(const migraphx::op::pooling& op) ...@@ -89,6 +91,13 @@ inline pooling_descriptor make_pooling(const migraphx::op::pooling& op)
return p; return p;
} }
inline lrn_descriptor make_lrn(const migraphx::op::lrn& op)
{
auto ldesc = make_obj<lrn_descriptor>(&miopenCreateLRNDescriptor);
miopenSetLRNDescriptor(ldesc.get(), miopenLRNCrossChannel, op.size, op.alpha, op.beta, op.bias);
return ldesc;
}
inline activation_descriptor make_relu() inline activation_descriptor make_relu()
{ {
auto ad = make_obj<activation_descriptor>(&miopenCreateActivationDescriptor); auto ad = make_obj<activation_descriptor>(&miopenCreateActivationDescriptor);
......
src/targets/gpu/include/migraphx/gpu/sub.hpp 0 → 100644
View file @ 85d789f7
#ifndef MIGRAPHX_GUARD_RTGLIB_SUB_HPP
#define MIGRAPHX_GUARD_RTGLIB_SUB_HPP
#include <migraphx/gpu/lowering.hpp>
#include <migraphx/gpu/oper.hpp>
#include <migraphx/manage_ptr.hpp>
#include <migraphx/instruction.hpp>
#include <migraphx/operators.hpp>
#include <migraphx/generate.hpp>
#include <migraphx/shape_for_each.hpp>
#include <migraphx/gpu/miopen.hpp>
#include <migraphx/gpu/hip.hpp>
#include <migraphx/dfor.hpp>
#include <migraphx/gpu/device/contiguous.hpp>
#include <migraphx/gpu/device/sub.hpp>
#include <migraphx/iterator_for.hpp>
#include <migraphx/gpu/rocblas.hpp>
#include <migraphx/gpu/context.hpp>
#include <migraphx/config.hpp>
#include <utility>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
struct hip_sub : binary_device<hip_sub, device::sub>
{
};
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif
src/targets/gpu/lowering.cpp
View file @ 85d789f7
...@@ -22,6 +22,7 @@ ...@@ -22,6 +22,7 @@
#include <migraphx/gpu/elu.hpp> #include <migraphx/gpu/elu.hpp>
#include <migraphx/gpu/softmax.hpp> #include <migraphx/gpu/softmax.hpp>
#include <migraphx/gpu/add.hpp> #include <migraphx/gpu/add.hpp>
#include <migraphx/gpu/sub.hpp>
#include <migraphx/gpu/exp.hpp> #include <migraphx/gpu/exp.hpp>
#include <migraphx/gpu/log.hpp> #include <migraphx/gpu/log.hpp>
#include <migraphx/gpu/sin.hpp> #include <migraphx/gpu/sin.hpp>
...@@ -42,6 +43,7 @@ ...@@ -42,6 +43,7 @@
#include <migraphx/gpu/concat.hpp> #include <migraphx/gpu/concat.hpp>
#include <migraphx/gpu/pad.hpp> #include <migraphx/gpu/pad.hpp>
#include <migraphx/gpu/gather.hpp> #include <migraphx/gpu/gather.hpp>
#include <migraphx/gpu/lrn.hpp>
#include <utility> #include <utility>
#include <functional> #include <functional>
#include <algorithm> #include <algorithm>
...@@ -55,6 +57,7 @@ struct miopen_apply ...@@ -55,6 +57,7 @@ struct miopen_apply
program* prog = nullptr; program* prog = nullptr;
context ctx{}; context ctx{};
std::unordered_map<std::string, std::function<instruction_ref(instruction_ref)>> apply_map{}; std::unordered_map<std::string, std::function<instruction_ref(instruction_ref)>> apply_map{};
instruction_ref last{};
void check_shape(shape x, instruction_ref i) void check_shape(shape x, instruction_ref i)
{ {
...@@ -65,6 +68,7 @@ struct miopen_apply ...@@ -65,6 +68,7 @@ struct miopen_apply
void init() void init()
{ {
this->last = instruction::get_output_alias(std::prev(prog->end()));
add_miopen_simple_op<miopen_relu>("relu", make_relu); add_miopen_simple_op<miopen_relu>("relu", make_relu);
add_miopen_simple_op<miopen_sigmoid>("sigmoid", make_sigmoid); add_miopen_simple_op<miopen_sigmoid>("sigmoid", make_sigmoid);
add_miopen_simple_op<miopen_abs>("abs", make_abs); add_miopen_simple_op<miopen_abs>("abs", make_abs);
...@@ -74,6 +78,7 @@ struct miopen_apply ...@@ -74,6 +78,7 @@ struct miopen_apply
add_miopen_extend_op<miopen_elu, op::elu>("elu", make_elu); add_miopen_extend_op<miopen_elu, op::elu>("elu", make_elu);
add_generic_op<hip_add>("add"); add_generic_op<hip_add>("add");
add_generic_op<hip_sub>("sub");
add_generic_op<hip_exp>("exp"); add_generic_op<hip_exp>("exp");
add_generic_op<hip_log>("log"); add_generic_op<hip_log>("log");
add_generic_op<hip_sin>("sin"); add_generic_op<hip_sin>("sin");
...@@ -95,6 +100,7 @@ struct miopen_apply ...@@ -95,6 +100,7 @@ struct miopen_apply
add_extend_op<hip_gather, op::gather>("gather"); add_extend_op<hip_gather, op::gather>("gather");
add_extend_op<hip_pad, op::pad>("pad"); add_extend_op<hip_pad, op::pad>("pad");
add_lrn_op();
add_convolution_op(); add_convolution_op();
add_pooling_op(); add_pooling_op();
add_batch_norm_inference_op(); add_batch_norm_inference_op();
...@@ -115,7 +121,7 @@ struct miopen_apply ...@@ -115,7 +121,7 @@ struct miopen_apply
instruction_ref insert_allocation(instruction_ref ins, const shape& s, std::string tag = "") instruction_ref insert_allocation(instruction_ref ins, const shape& s, std::string tag = "")
{ {
if(ins == --prog->end() and tag.empty()) if(ins == last and tag.empty())
{ {
return prog->add_parameter("output", s); return prog->add_parameter("output", s);
} }
...@@ -155,6 +161,17 @@ struct miopen_apply ...@@ -155,6 +161,17 @@ struct miopen_apply
}); });
} }
void add_lrn_op()
{
apply_map.emplace("lrn", [=](instruction_ref ins) {
auto&& op = any_cast<op::lrn>(ins->get_operator());
auto ldesc = make_lrn(op);
auto output = insert_allocation(ins, ins->get_shape());
return prog->replace_instruction(
ins, miopen_lrn{std::move(ldesc)}, ins->inputs().at(0), output);
});
}
template <class T> template <class T>
void add_generic_op(std::string name) void add_generic_op(std::string name)
{ {
......
src/targets/gpu/lrn.cpp 0 → 100644
View file @ 85d789f7
#include <migraphx/gpu/lrn.hpp>
#include <migraphx/operators.hpp>
#include <migraphx/manage_ptr.hpp>
#include <migraphx/gpu/miopen.hpp>
#include <utility>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
shape miopen_lrn::compute_shape(const std::vector<shape>& inputs) const
{
check_shapes{inputs, *this}.has(2).not_broadcasted();
return inputs.at(1);
}
argument miopen_lrn::compute(context& ctx,
const shape& output_shape,
const std::vector<argument>& args) const
{
float alpha = 1;
float beta = 0;
auto x_desc = make_tensor(args[0].get_shape());
auto y_desc = make_tensor(output_shape);
miopenLRNForward(ctx.get_stream().get_miopen(),
ldesc.get(),
&alpha,
x_desc.get(),
args[0].implicit(),
&beta,
y_desc.get(),
args[1].implicit(),
false,
nullptr);
return args[1];
}
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
src/targets/gpu/target.cpp
View file @ 85d789f7
...@@ -15,6 +15,7 @@ ...@@ -15,6 +15,7 @@
#include <migraphx/eliminate_contiguous.hpp> #include <migraphx/eliminate_contiguous.hpp>
#include <migraphx/common_subexpression_elimination.hpp> #include <migraphx/common_subexpression_elimination.hpp>
#include <migraphx/fwd_conv_batchnorm_rewrite.hpp> #include <migraphx/fwd_conv_batchnorm_rewrite.hpp>
#include <migraphx/rewrite_rnn.hpp>
#include <migraphx/eliminate_concat.hpp> #include <migraphx/eliminate_concat.hpp>
#include <migraphx/gpu/concat_gpu_opt.hpp> #include <migraphx/gpu/concat_gpu_opt.hpp>
...@@ -31,14 +32,16 @@ std::vector<pass> target::get_passes(migraphx::context& gctx) const ...@@ -31,14 +32,16 @@ std::vector<pass> target::get_passes(migraphx::context& gctx) const
dead_code_elimination{}, dead_code_elimination{},
fwd_conv_batchnorm_rewrite{}, fwd_conv_batchnorm_rewrite{},
dead_code_elimination{}, dead_code_elimination{},
common_subexpression_elimination{}, rewrite_rnn{},
dead_code_elimination{}, dead_code_elimination{},
//common_subexpression_elimination{},
//dead_code_elimination{},
simplify_algebra{}, simplify_algebra{},
dead_code_elimination{}, dead_code_elimination{},
constant_propagate{}, constant_propagate{},
dead_code_elimination{}, dead_code_elimination{},
auto_contiguous{}, auto_contiguous{},
simplify_reshapes{}, //simplify_reshapes{},
dead_code_elimination{}, dead_code_elimination{},
lowering{ctx}, lowering{ctx},
eliminate_concat{concat_gpu_optimization{}}, eliminate_concat{concat_gpu_optimization{}},
......
src/tf/tf.cpp
View file @ 85d789f7
...@@ -175,10 +175,8 @@ struct tf_parser ...@@ -175,10 +175,8 @@ struct tf_parser
instruction_ref instruction_ref
parse_biasadd(const std::string&, attribute_map, std::vector<instruction_ref> args) parse_biasadd(const std::string&, attribute_map, std::vector<instruction_ref> args)
{ {
// assume second arg is bias uint64_t axis = 1;
std::vector<int64_t> dims; auto l0 = prog.add_instruction(op::broadcast{axis, args[0]->get_shape()}, args[1]);
copy(args[0]->get_shape().lens(), std::back_inserter(dims));
auto l0 = prog.add_instruction(op::reshape{dims}, args[1]);
return prog.add_instruction(op::add{}, args[0], l0); return prog.add_instruction(op::add{}, args[0], l0);
} }
...@@ -519,7 +517,33 @@ struct tf_parser ...@@ -519,7 +517,33 @@ struct tf_parser
break; // throw std::runtime_error("Unsupported type VARIANT"); break; // throw std::runtime_error("Unsupported type VARIANT");
case tensorflow::DataType::DT_UINT32: shape_type = shape::uint32_type; break; case tensorflow::DataType::DT_UINT32: shape_type = shape::uint32_type; break;
case tensorflow::DataType::DT_UINT64: shape_type = shape::uint64_type; break; case tensorflow::DataType::DT_UINT64: shape_type = shape::uint64_type; break;
default: break;
// tf pb should not use these types
case tensorflow::DataType::DT_FLOAT_REF: break;
case tensorflow::DataType::DT_DOUBLE_REF: break;
case tensorflow::DataType::DT_INT32_REF: break;
case tensorflow::DataType::DT_UINT8_REF: break;
case tensorflow::DataType::DT_INT16_REF: break;
case tensorflow::DataType::DT_INT8_REF: break;
case tensorflow::DataType::DT_STRING_REF: break;
case tensorflow::DataType::DT_COMPLEX64_REF: break;
case tensorflow::DataType::DT_INT64_REF: break;
case tensorflow::DataType::DT_BOOL_REF: break;
case tensorflow::DataType::DT_QINT8_REF: break;
case tensorflow::DataType::DT_QUINT8_REF: break;
case tensorflow::DataType::DT_QINT32_REF: break;
case tensorflow::DataType::DT_BFLOAT16_REF: break;
case tensorflow::DataType::DT_QINT16_REF: break;
case tensorflow::DataType::DT_QUINT16_REF: break;
case tensorflow::DataType::DT_UINT16_REF: break;
case tensorflow::DataType::DT_COMPLEX128_REF: break;
case tensorflow::DataType::DT_HALF_REF: break;
case tensorflow::DataType::DT_RESOURCE_REF: break;
case tensorflow::DataType::DT_VARIANT_REF: break;
case tensorflow::DataType::DT_UINT32_REF: break;
case tensorflow::DataType::DT_UINT64_REF: break;
case tensorflow::DataType::DataType_INT_MAX_SENTINEL_DO_NOT_USE_: break;
case tensorflow::DataType::DataType_INT_MIN_SENTINEL_DO_NOT_USE_: break;
} }
return shape_type; return shape_type;
} }
...@@ -559,7 +583,39 @@ struct tf_parser ...@@ -559,7 +583,39 @@ struct tf_parser
case tensorflow::DataType::DT_UINT64: throw std::runtime_error(""); case tensorflow::DataType::DT_UINT64: throw std::runtime_error("");
case tensorflow::DataType::DT_COMPLEX64: throw std::runtime_error(""); case tensorflow::DataType::DT_COMPLEX64: throw std::runtime_error("");
case tensorflow::DataType::DT_COMPLEX128: throw std::runtime_error(""); case tensorflow::DataType::DT_COMPLEX128: throw std::runtime_error("");
default: break; case tensorflow::DataType::DT_QINT8: throw std::runtime_error("");
case tensorflow::DataType::DT_QUINT8: throw std::runtime_error("");
case tensorflow::DataType::DT_QINT32: throw std::runtime_error("");
case tensorflow::DataType::DT_BFLOAT16: throw std::runtime_error("");
case tensorflow::DataType::DT_QINT16: throw std::runtime_error("");
case tensorflow::DataType::DT_QUINT16: throw std::runtime_error("");
case tensorflow::DataType::DT_RESOURCE: throw std::runtime_error("");
case tensorflow::DataType::DT_VARIANT: throw std::runtime_error("");
case tensorflow::DataType::DT_FLOAT_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_DOUBLE_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_INT32_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_UINT8_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_INT16_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_INT8_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_STRING_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_COMPLEX64_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_INT64_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_BOOL_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_QINT8_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_QUINT8_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_QINT32_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_BFLOAT16_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_QINT16_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_QUINT16_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_UINT16_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_COMPLEX128_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_HALF_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_RESOURCE_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_VARIANT_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_UINT32_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_UINT64_REF: throw std::runtime_error("");
case tensorflow::DataType::DataType_INT_MAX_SENTINEL_DO_NOT_USE_: throw std::runtime_error("");
case tensorflow::DataType::DataType_INT_MIN_SENTINEL_DO_NOT_USE_: throw std::runtime_error("");
} }
MIGRAPHX_THROW("Invalid tensor type"); MIGRAPHX_THROW("Invalid tensor type");
} }
...@@ -591,7 +647,39 @@ struct tf_parser ...@@ -591,7 +647,39 @@ struct tf_parser
case tensorflow::DataType::DT_UINT64: throw std::runtime_error(""); case tensorflow::DataType::DT_UINT64: throw std::runtime_error("");
case tensorflow::DataType::DT_COMPLEX64: throw std::runtime_error(""); case tensorflow::DataType::DT_COMPLEX64: throw std::runtime_error("");
case tensorflow::DataType::DT_COMPLEX128: throw std::runtime_error(""); case tensorflow::DataType::DT_COMPLEX128: throw std::runtime_error("");
default: break; case tensorflow::DataType::DT_QINT8: throw std::runtime_error("");
case tensorflow::DataType::DT_QUINT8: throw std::runtime_error("");
case tensorflow::DataType::DT_QINT32: throw std::runtime_error("");
case tensorflow::DataType::DT_BFLOAT16: throw std::runtime_error("");
case tensorflow::DataType::DT_QINT16: throw std::runtime_error("");
case tensorflow::DataType::DT_QUINT16: throw std::runtime_error("");
case tensorflow::DataType::DT_RESOURCE: throw std::runtime_error("");
case tensorflow::DataType::DT_VARIANT: throw std::runtime_error("");
case tensorflow::DataType::DT_FLOAT_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_DOUBLE_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_INT32_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_UINT8_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_INT16_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_INT8_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_STRING_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_COMPLEX64_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_INT64_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_BOOL_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_QINT8_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_QUINT8_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_QINT32_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_BFLOAT16_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_QINT16_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_QUINT16_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_UINT16_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_COMPLEX128_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_HALF_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_RESOURCE_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_VARIANT_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_UINT32_REF: throw std::runtime_error("");
case tensorflow::DataType::DT_UINT64_REF: throw std::runtime_error("");
case tensorflow::DataType::DataType_INT_MAX_SENTINEL_DO_NOT_USE_: throw std::runtime_error("");
case tensorflow::DataType::DataType_INT_MIN_SENTINEL_DO_NOT_USE_: throw std::runtime_error("");
} }
MIGRAPHX_THROW("Invalid tensor type"); MIGRAPHX_THROW("Invalid tensor type");
} }
......
test/CMakeLists.txt
View file @ 85d789f7
...@@ -112,7 +112,8 @@ if(MIGRAPHX_ENABLE_GPU) ...@@ -112,7 +112,8 @@ if(MIGRAPHX_ENABLE_GPU)
endif() endif()
# Onnx test # Onnx test
add_executable(test_onnx onnx/onnx_test.cpp) set(TEST_ONNX_DIR ${CMAKE_CURRENT_SOURCE_DIR}/onnx)
add_executable(test_onnx ${TEST_ONNX_DIR}/onnx_test.cpp)
rocm_clang_tidy_check(test_onnx) rocm_clang_tidy_check(test_onnx)
target_link_libraries(test_onnx migraphx_onnx) target_link_libraries(test_onnx migraphx_onnx)
target_include_directories(test_onnx PUBLIC include) target_include_directories(test_onnx PUBLIC include)
...@@ -129,6 +130,10 @@ add_test(NAME test_tf COMMAND $<TARGET_FILE:test_tf> WORKING_DIRECTORY ${CMAKE_C ...@@ -129,6 +130,10 @@ add_test(NAME test_tf COMMAND $<TARGET_FILE:test_tf> WORKING_DIRECTORY ${CMAKE_C
add_dependencies(tests test_tf) add_dependencies(tests test_tf)
add_dependencies(check test_tf) add_dependencies(check test_tf)
if(MIGRAPHX_ENABLE_PYTHON)
add_subdirectory(py)
endif()
function(test_header NAME HEADER) function(test_header NAME HEADER)
file(WRITE ${CMAKE_CURRENT_BINARY_DIR}/header-main-include-${NAME}.cpp file(WRITE ${CMAKE_CURRENT_BINARY_DIR}/header-main-include-${NAME}.cpp
......
test/cpu_ops_test.cpp
View file @ 85d789f7
...@@ -5,6 +5,7 @@ ...@@ -5,6 +5,7 @@
#include <migraphx/instruction.hpp> #include <migraphx/instruction.hpp>
#include <migraphx/cpu/target.hpp> #include <migraphx/cpu/target.hpp>
#include <migraphx/verify.hpp> #include <migraphx/verify.hpp>
#include <migraphx/onnx.hpp>
#include "test.hpp" #include "test.hpp"
float sigmoid(float x) { return 1 / (1 + expf(-x)); } float sigmoid(float x) { return 1 / (1 + expf(-x)); }
...@@ -731,6 +732,20 @@ TEST_CASE(leaky_relu_test) ...@@ -731,6 +732,20 @@ TEST_CASE(leaky_relu_test)
EXPECT(migraphx::verify_range(results_vector, gold)); EXPECT(migraphx::verify_range(results_vector, gold));
} }
TEST_CASE(lrn_test)
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {1, 5, 1, 1}};
auto l = p.add_literal(migraphx::literal{s, {-2.0f, 1.0f, 0.f, 1.0f, 2.0f}});
p.add_instruction(migraphx::op::lrn{0.0001, 0.75, 1, 5}, l);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<float> results_vector(5);
result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
std::vector<float> gold = {-2 / 1.000075, 1 / 1.00009, 0 / 1.000145, 1 / 1.00009, 2 / 1.000075};
EXPECT(migraphx::verify_range(results_vector, gold));
}
TEST_CASE(imagescaler_test) TEST_CASE(imagescaler_test)
{ {
migraphx::program p; migraphx::program p;
......
test/cpu_rnn_ops_test.cpp 0 → 100644
View file @ 85d789f7
This diff is collapsed.
test/dead_code_elimination_test.cpp
View file @ 85d789f7
#include <migraphx/dead_code_elimination.hpp> #include <migraphx/dead_code_elimination.hpp>
#include <basic_ops.hpp> #include <basic_ops.hpp>
#include <migraphx/operators.hpp>
#include <test.hpp> #include <test.hpp>
struct dce_target struct dce_target
...@@ -111,4 +112,21 @@ TEST_CASE(depth_test) ...@@ -111,4 +112,21 @@ TEST_CASE(depth_test)
EXPECT(result != migraphx::literal{4}); EXPECT(result != migraphx::literal{4});
} }
TEST_CASE(undefined_test)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto undef = p.add_instruction(migraphx::op::undefined{});
p.add_instruction(sum_op{}, one, two);
auto count = std::distance(p.begin(), p.end());
p.compile(dce_target{});
EXPECT(std::distance(p.begin(), p.end()) == count - 1);
EXPECT(not p.has_instruction(undef));
auto result = p.eval({});
EXPECT(result == migraphx::literal{3});
EXPECT(result != migraphx::literal{4});
}
int main(int argc, const char* argv[]) { test::run(argc, argv); } int main(int argc, const char* argv[]) { test::run(argc, argv); }
test/gpu/miopen.cpp
View file @ 85d789f7
This diff is collapsed.
test/memory_coloring_test.cpp
View file @ 85d789f7
...@@ -78,7 +78,7 @@ TEST_CASE(test3) ...@@ -78,7 +78,7 @@ TEST_CASE(test3)
auto p3 = add_alloc(p, {migraphx::shape::float_type, {40}}); auto p3 = add_alloc(p, {migraphx::shape::float_type, {40}});
p.add_instruction(pass_op{}, p3, p1); p.add_instruction(pass_op{}, p3, p1);
p.compile(memory_coloring_target{}); p.compile(memory_coloring_target{});
CHECK(p.get_parameter_shape("scratch").bytes() == 704); // The optimal solution is actually 672 CHECK(p.get_parameter_shape("scratch").bytes() == 672);
CHECK(no_allocate(p)); CHECK(no_allocate(p));
} }
...@@ -487,7 +487,7 @@ TEST_CASE(test33) ...@@ -487,7 +487,7 @@ TEST_CASE(test33)
auto a5 = add_alloc(p, {migraphx::shape::float_type, {40}}); auto a5 = add_alloc(p, {migraphx::shape::float_type, {40}});
p.add_instruction(pass_op{}, a5, p1); p.add_instruction(pass_op{}, a5, p1);
p.compile(memory_coloring_target{}); p.compile(memory_coloring_target{});
CHECK(p.get_parameter_shape("scratch").bytes() == 224); CHECK(p.get_parameter_shape("scratch").bytes() == 192);
CHECK(no_allocate(p)); CHECK(no_allocate(p));
} }
...@@ -594,7 +594,7 @@ TEST_CASE(test38) ...@@ -594,7 +594,7 @@ TEST_CASE(test38)
auto p83 = p.add_instruction(pass_op{}, p78, p77); auto p83 = p.add_instruction(pass_op{}, p78, p77);
p.add_instruction(pass_op{}, output, p83, p63); p.add_instruction(pass_op{}, output, p83, p63);
p.compile(memory_coloring_target{}); p.compile(memory_coloring_target{});
CHECK(p.get_parameter_shape("scratch").bytes() == 6422528); CHECK(p.get_parameter_shape("scratch").bytes() == 7225344); // Optimal solution is 6422528
CHECK(no_allocate(p)); CHECK(no_allocate(p));
} }
......
test/onnx/implicit_sub_bcast_test.onnx 0 → 100644
View file @ 85d789f7
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