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submodule
ngraph
Commits
f5d2fa68
Commit
f5d2fa68
authored
Sep 25, 2018
by
shssf
Committed by
Robert Kimball
Sep 25, 2018
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IntelGPU backend: Types workaround removal (#1681)
* IntelGPU backend: Types workaround removal * PR1681. Fix style
parent
7ebf7157
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Showing
2 changed files
with
10 additions
and
22 deletions
+10
-22
intelgpu_layout.cpp
src/ngraph/runtime/intelgpu/intelgpu_layout.cpp
+10
-16
unit_test.manifest
src/ngraph/runtime/intelgpu/unit_test.manifest
+0
-6
No files found.
src/ngraph/runtime/intelgpu/intelgpu_layout.cpp
View file @
f5d2fa68
...
...
@@ -62,6 +62,14 @@ cldnn::data_types
{
return
cldnn
::
data_types
::
u8
;
}
else
if
(
element_type
==
ngraph
::
element
::
i32
)
{
return
cldnn
::
data_types
::
i32
;
}
else
if
(
element_type
==
ngraph
::
element
::
i64
)
{
return
cldnn
::
data_types
::
i64
;
}
else
if
(
element_type
==
ngraph
::
element
::
f32
)
{
return
cldnn
::
data_types
::
f32
;
...
...
@@ -120,22 +128,8 @@ cldnn::layout runtime::intelgpu::IntelGPULayout::create_cldnn_layout(
const
ngraph
::
element
::
Type
&
element_type
,
const
Shape
&
element_shape
)
{
const
cldnn
::
format
::
type
format
=
cldnn
::
format
::
bfyx
;
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
);
}
const
cldnn
::
data_types
data_type
=
get_cldnn_type
(
element_type
);
const
cldnn
::
tensor
tensor
=
create_cldnn_tensor
(
element_shape
);
return
cldnn
::
layout
(
data_type
,
format
,
tensor
);
}
...
...
src/ngraph/runtime/intelgpu/unit_test.manifest
View file @
f5d2fa68
...
...
@@ -2,26 +2,20 @@ argmax_trivial
argmin_trivial
avg_pool_2d_2channel_2image_padded_only_above
avg_pool_3d
backwards_acos
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
backwards_replace_slice
backwards_reverse_sequence_n3_c2_h3
backwards_reverse_sequence_n4d2c3h2w2
backwards_sign
backwards_slice
backwards_tanh
batch_norm_one_output
batch_norm_three_outputs
concat_matrix_int64
divide_by_zero_int32
dot_matrix_vector_int64
function_call
...
...
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