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Commit 446cf07b authored by shssf's avatar shssf Committed by Robert Kimball
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IntelGPU backend: Workaround for unsupported data types (#1572)

parent b21ff63d
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Inline Side-by-side
Showing with 66 additions and 58 deletions
src/ngraph/runtime/intelgpu/intelgpu_backend.cpp
View file @ 446cf07b
......@@ -109,15 +109,6 @@ static const element::Type& get_output_type(const shared_ptr<Node>& op, size_t n
return op->get_outputs().at(num).get_tensor().get_element_type();
}
static void argument_type_check(const element::Type& type)
{
if (type != element::f32 && type != element::boolean)
{
throw invalid_argument("Kernel data type \"" + type.c_type_string() +
"\" is not supported.");
}
}
static void do_eltwise_operation(cldnn::topology& topology,
const shared_ptr<Node>& op,
cldnn::eltwise_mode mode)
......@@ -168,16 +159,13 @@ static void do_logical_operation(cldnn::topology& topology,
const string& operation)
{
arguments_check(op, 2, 1);
argument_type_check(get_input_type(op, 0));
argument_type_check(get_input_type(op, 1));
runtime::intelgpu::do_logic_kernel(topology,
get_input_name(op, 0),
get_input_shape(op, 0),
get_input_type(op, 0).c_type_string(),
get_input_type(op, 0),
get_input_name(op, 1),
get_input_shape(op, 1),
get_input_type(op, 1).c_type_string(),
get_output_name(op),
get_output_shape(op),
get_output_type(op),
......@@ -548,6 +536,7 @@ bool runtime::intelgpu::IntelGPUBackend::compile(shared_ptr<Function> func)
do_bcast_sum_operation(topology,
get_input_name(op),
get_input_shape(op),
get_input_type(op),
get_output_name(op),
get_output_shape(op),
get_output_type(op),
......@@ -571,6 +560,7 @@ bool runtime::intelgpu::IntelGPUBackend::compile(shared_ptr<Function> func)
do_bcast_sum_operation(topology,
get_input_name(op),
get_input_shape(op),
get_input_type(op),
get_output_name(op),
get_output_shape(op),
get_output_type(op),
......
src/ngraph/runtime/intelgpu/intelgpu_layout.cpp
View file @ 446cf07b
......@@ -123,9 +123,23 @@ cldnn::tensor runtime::intelgpu::IntelGPULayout::create_cldnn_offset(const Shape
cldnn::layout runtime::intelgpu::IntelGPULayout::create_cldnn_layout(
const ngraph::element::Type& element_type, const Shape& element_shape)
{
const cldnn::data_types data_type = get_cldnn_type(element_type);
const cldnn::format::type format = cldnn::format::bfyx;
const cldnn::tensor tensor = create_cldnn_tensor(element_shape);
cldnn::data_types data_type;
cldnn::tensor tensor;
// This is workaround for data types that are not supported by clDNN
// If the type is not supported, it treated as char*
// Example, "int64_t input[2, 3, 4]" will be "char input[192]"
if ((element_type == ngraph::element::i64) || (element_type == ngraph::element::i32))
{
data_type = cldnn::data_types::i8;
tensor = create_cldnn_tensor({shape_size(element_shape) * element_type.size()});
}
else
{
data_type = get_cldnn_type(element_type);
tensor = create_cldnn_tensor(element_shape);
}
return cldnn::layout(data_type, format, tensor);
}
......
src/ngraph/runtime/intelgpu/intelgpu_op_broadcast.cpp
View file @ 446cf07b
......@@ -31,6 +31,7 @@ using namespace ngraph;
void runtime::intelgpu::do_bcast_sum_operation(cldnn::topology& topology,
const string& input_name,
const Shape& input_shape,
const element::Type& input_type,
const string& output_name,
const Shape& output_shape,
const element::Type& output_type,
......@@ -42,8 +43,12 @@ void runtime::intelgpu::do_bcast_sum_operation(cldnn::topology& topology,
codegen::CodeWriter writer;
vector<size_t> gws;
runtime::intelgpu::gen_func_def(
writer, function_name, {"float"}, {input_shape}, "float", output_shape);
runtime::intelgpu::gen_func_def(writer,
function_name,
{get_opencl_type_name(input_type)},
{input_shape},
get_opencl_type_name(output_type),
output_shape);
writer.block_begin();
{
if (is_bcast)
......@@ -63,7 +68,11 @@ void runtime::intelgpu::do_bcast_sum_operation(cldnn::topology& topology,
"output" + access_dims(input_shape, "i", axis) + " = result;\n";
// Generate loops related to input order with GWS
gws = generate_loops_w_axes(writer, input_shape, true, axis, "float result = 0.0f;\n");
gws = generate_loops_w_axes(writer,
input_shape,
true,
axis,
get_opencl_type_name(output_type) + " result = 0.0f;\n");
writer << "result += input0" << access_dims(input_shape) << ";\n";
......
src/ngraph/runtime/intelgpu/intelgpu_op_broadcast.hpp
View file @ 446cf07b
......@@ -33,6 +33,7 @@ namespace ngraph
void do_bcast_sum_operation(cldnn::topology& topology,
const std::string& input_name,
const Shape& input_shape,
const element::Type& input_type,
const std::string& output_name,
const Shape& output_shape,
const element::Type& output_type,
......
src/ngraph/runtime/intelgpu/intelgpu_op_custom_kernels.cpp
View file @ 446cf07b
......@@ -26,6 +26,22 @@
using namespace std;
using namespace ngraph;
string runtime::intelgpu::get_opencl_type_name(const element::Type& ngraph_type)
{
if (ngraph_type == ngraph::element::i64)
{
return "long";
}
else if (ngraph_type == ngraph::element::i32)
{
return "int";
}
else
{
return ngraph_type.c_type_string();
}
}
vector<cldnn_arg> runtime::intelgpu::get_kernel_args(size_t input, size_t output)
{
vector<cldnn_arg> result;
......@@ -1094,10 +1110,9 @@ void runtime::intelgpu::do_select_operation(cldnn::topology& topology,
void runtime::intelgpu::do_logic_kernel(cldnn::topology& topology,
const string& input0_name,
const Shape& input0_shape,
const string& input0_type,
const element::Type& input0_type,
const string& input1_name,
const Shape& input1_shape,
const string& input1_type,
const string& output_name,
const Shape& output_shape,
const element::Type& output_type,
......@@ -1110,9 +1125,9 @@ void runtime::intelgpu::do_logic_kernel(cldnn::topology& topology,
gen_func_def(writer,
entry_point_name,
{2, input0_type},
{2, get_opencl_type_name(input0_type)},
{input0_shape, input1_shape},
"char",
get_opencl_type_name(output_type),
output_shape);
writer.block_begin();
......@@ -1228,9 +1243,9 @@ void runtime::intelgpu::do_one_hot_operation(cldnn::topology& topology,
gen_func_def(writer,
entry_point_name,
{input_type.c_type_string()},
{get_opencl_type_name(input_type)},
{input_shape},
output_type.c_type_string(),
get_opencl_type_name(output_type),
output_shape);
writer.block_begin();
......@@ -1286,8 +1301,8 @@ void runtime::intelgpu::do_convert_operation(cldnn::topology& topology,
{
const cldnn::layout layout = IntelGPULayout::create_cldnn_layout(output_type, output_shape);
const string entry_point_name = "convert_" + output_name;
const string& input_type_name = input_type.c_type_string();
const string& output_type_name = output_type.c_type_string();
const string& input_type_name = get_opencl_type_name(input_type);
const string& output_type_name = get_opencl_type_name(output_type);
codegen::CodeWriter writer;
vector<size_t> gws;
......
src/ngraph/runtime/intelgpu/intelgpu_op_custom_kernels.hpp
View file @ 446cf07b
......@@ -96,12 +96,11 @@ namespace ngraph
const element::Type& output_type);
void do_logic_kernel(cldnn::topology& topology,
const std::string& inputA_name,
const Shape& inputA_shape,
const std::string& inputA_type,
const std::string& inputB_name,
const Shape& inputB_shape,
const std::string& inputB_type,
const std::string& input0_name,
const Shape& input0_shape,
const element::Type& input0_type,
const std::string& input1_name,
const Shape& input1_shape,
const std::string& output_name,
const Shape& output_shape,
const element::Type& output_type,
......@@ -149,6 +148,7 @@ namespace ngraph
const element::Type& output_type);
// Helper functions used in cldnn::custom_gpu_primitive kernels
std::string get_opencl_type_name(const element::Type& ngraph_type);
std::vector<cldnn_arg> get_kernel_args(size_t input, size_t output);
std::string array_dims(const Shape& dimentions, const AxisSet& axis = {});
std::string access_dims(const Shape& dimentions,
......
src/ngraph/runtime/intelgpu/unit_test.manifest
View file @ 446cf07b
abc_int64
aliased_output
argmax_trivial
argmin_trivial
atan
avg_pool_2d_2channel_2image_padded_only_above
avg_pool_3d
backwards_abs
backwards_acos
backwards_atan
backwards_avgpool_n1_c1_hw2x2
backwards_avgpool_n1_c1_hw4x4
backwards_avgpool_n2_c2_hw4x4
backwards_batch_norm_three_outputs
backwards_ceiling
backwards_dot_scalar_tensor
backwards_dot_tensor3_tensor3
backwards_dot_tensor_scalar
backwards_dot_tensor_vector
backwards_exp
backwards_floor
backwards_maxpool_n2_c1_hw5_3x3_str2_max
backwards_maxpool_n4_c1_hw4_2x2_max
......@@ -24,15 +21,11 @@ backwards_reverse_sequence_n4d2c3h2w2
backwards_sign
backwards_slice
backwards_tan
backwards_tanh
batch_norm_one_output
batch_norm_three_outputs
broadcast_vector_rowwise_int64
ceiling
concat_matrix_int64
constant_multi_use
convert_int32_bool
convert_int32_float32
convolution_outlining
divide_by_zero_int32
dot_matrix_vector_int64
floor
......@@ -41,15 +34,6 @@ lrn
max_pool_3d
numeric_double_inf
numeric_double_nan
one_hot_matrix_0
one_hot_scalar_0_in_3
one_hot_scalar_1_in_3
one_hot_scalar_2_in_3
one_hot_scalar_oob_in_3
one_hot_vector_0
one_hot_vector_1
one_hot_vector_1_barely_oob
one_hot_vector_1_far_oob
reduce_3d_to_vector
reduce_matrix_cols_zero
reduce_matrix_columns
......@@ -74,16 +58,11 @@ reshape_6d
reverse_sequence_n2c3h4w2
reverse_sequence_n4c3h2w2
reverse_sequence_n4d2c3h2w2
scalar_constant_int64
select_and_scatter_3d_without_overlap
select_and_scatter_without_overlap
select_and_scatter_with_overlap
select_and_scatter_without_overlap
sign
tan
tensor_2constant
tensor_constant_int64
validate_call_input_type
validate_call_output_type
zero_sized_abs
zero_sized_acos
zero_sized_add
......
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