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XeratecXeratec
committed
Improve C tensor naming
1 parent 791c2e6 commit d3b052d

21 files changed

+215
-215
lines changed

‎Deeploy/Targets/CortexM/Templates/GEMMTemplate.py‎

Lines changed: 7 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -31,14 +31,14 @@ def alignToContext(self, ctxt: NetworkContext,
3131

3232
Linear_8_Template = _GEMM_8_Template("""
3333
// GEMM
34-
int8_t* ref_${data_out}_${A} = ${A};
35-
int8_t* ref_${data_out}_${B} = ${B};
36-
int8_t* ref_${data_out}_${data_out} = ${data_out};
34+
int8_t* ref_${nodeName}_${A} = ${A};
35+
int8_t* ref_${nodeName}_${B} = ${B};
36+
int8_t* ref_${nodeName}_${data_out} = ${data_out};
3737
for(int i=0;i<${batch};i++){
38-
arm_fully_connected_s8(&${ctxt}, &${fc_params}, &${quant_params}, &${input_dims}, ref_${data_out}_${A}, &${filter_dims}, ref_${data_out}_${B}, &${bias_dims}, ${C}, &${output_dims}, ref_${data_out}_${data_out});
39-
ref_${data_out}_${A} += ${M} * ${N};
40-
ref_${data_out}_${B} += ${N} * ${O};
41-
ref_${data_out}_${data_out} += ${M} * ${O};
38+
arm_fully_connected_s8(&${ctxt}, &${fc_params}, &${quant_params}, &${input_dims}, ref_${nodeName}_${A}, &${filter_dims}, ref_${nodeName}_${B}, &${bias_dims}, ${C}, &${output_dims}, ref_${nodeName}_${data_out});
39+
ref_${nodeName}_${A} += ${M} * ${N};
40+
ref_${nodeName}_${B} += ${N} * ${O};
41+
ref_${nodeName}_${data_out} += ${M} * ${O};
4242
}
4343
""")
4444

‎Deeploy/Targets/Generic/Templates/ConvTemplate.py‎

Lines changed: 12 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -36,18 +36,18 @@ def alignToContext(self, ctxt: NetworkContext,
3636
3737
// 1D Conv (Name: ${nodeName}, Op: ${nodeOp})
3838
BEGIN_SINGLE_CORE
39-
${data_in_type.typeName} ref_${data_out}_${data_in} = ${data_in};
40-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
39+
${data_in_type.typeName} ref_${nodeName}_${data_in} = ${data_in};
40+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
4141
4242
for (uint32_t n=0; n<${batch}; ++n) {
4343
Conv2d_s${data_in_type.referencedType.typeWidth}_s${weight_type.referencedType.typeWidth}_s${data_out_type.referencedType.typeWidth}_NCHW(
44-
ref_${data_out}_${data_in}, ${ch_im_in}, 1, ${dim_im_in_y},
44+
ref_${nodeName}_${data_in}, ${ch_im_in}, 1, ${dim_im_in_y},
4545
${weight}, ${ch_im_out}, 1, ${dim_kernel_y},
4646
1, ${stride_y},
47-
ref_${data_out}_${data_out}, ${input_offset}, ${output_offset}
47+
ref_${nodeName}_${data_out}, ${input_offset}, ${output_offset}
4848
);
49-
ref_${data_out}_${data_in} += ${batchOffsetIn};
50-
ref_${data_out}_${data_out} += ${batchOffsetOut};
49+
ref_${nodeName}_${data_in} += ${batchOffsetIn};
50+
ref_${nodeName}_${data_out} += ${batchOffsetOut};
5151
}
5252
END_SINGLE_CORE
5353
""")
@@ -60,18 +60,18 @@ def alignToContext(self, ctxt: NetworkContext,
6060
6161
// 2D Conv (Name: ${nodeName}, Op: ${nodeOp})
6262
BEGIN_SINGLE_CORE
63-
${data_in_type.typeName} ref_${data_out}_${data_in} = ${data_in};
64-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
63+
${data_in_type.typeName} ref_${nodeName}_${data_in} = ${data_in};
64+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
6565
6666
for (uint32_t n=0; n<${batch}; ++n) {
6767
Conv2d_s${data_in_type.referencedType.typeWidth}_s${weight_type.referencedType.typeWidth}_s${data_out_type.referencedType.typeWidth}_NCHW(
68-
ref_${data_out}_${data_in}, ${ch_im_in}, ${dim_im_in_x}, ${dim_im_in_y},
68+
ref_${nodeName}_${data_in}, ${ch_im_in}, ${dim_im_in_x}, ${dim_im_in_y},
6969
${weight}, ${ch_im_out}, ${dim_kernel_x}, ${dim_kernel_y},
7070
${stride_x}, ${stride_y},
71-
ref_${data_out}_${data_out}, ${input_offset}, ${output_offset}
71+
ref_${nodeName}_${data_out}, ${input_offset}, ${output_offset}
7272
);
73-
ref_${data_out}_${data_in} += ${batchOffsetIn};
74-
ref_${data_out}_${data_out} += ${batchOffsetOut};
73+
ref_${nodeName}_${data_in} += ${batchOffsetIn};
74+
ref_${nodeName}_${data_out} += ${batchOffsetOut};
7575
}
7676
END_SINGLE_CORE
7777
""")

‎Deeploy/Targets/Generic/Templates/ConvTransposeTemplate.py‎

Lines changed: 6 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -12,20 +12,20 @@
1212
1313
// 1D Transposed Conv (Name: ${nodeName}, Op: ${nodeOp})
1414
BEGIN_SINGLE_CORE
15-
${data_in_type.typeName} ref_${data_out}_${data_in} = ${data_in};
16-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
15+
${data_in_type.typeName} ref_${nodeName}_${data_in} = ${data_in};
16+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
1717
1818
for (uint32_t n=0; n<${batch}; ++n) {
1919
ConvTranspose1d_fp32(
20-
ref_${data_out}_${data_in}, ${ch_im_in}, ${dim_im_in_y},
20+
ref_${nodeName}_${data_in}, ${ch_im_in}, ${dim_im_in_y},
2121
${weight}, ${ch_im_out}, ${dim_kernel_y},
2222
${stride_y},
2323
${bias}, ${has_bias},
24-
ref_${data_out}_${data_out}, ${dim_im_out_y}
24+
ref_${nodeName}_${data_out}, ${dim_im_out_y}
2525
);
2626
27-
ref_${data_out}_${data_in} += ${batchOffsetIn};
28-
ref_${data_out}_${data_out} += ${batchOffsetOut};
27+
ref_${nodeName}_${data_in} += ${batchOffsetIn};
28+
ref_${nodeName}_${data_out} += ${batchOffsetOut};
2929
}
3030
END_SINGLE_CORE
3131
""")

‎Deeploy/Targets/Generic/Templates/DWConvTemplate.py‎

Lines changed: 12 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -36,18 +36,18 @@ def alignToContext(self, ctxt: NetworkContext,
3636
3737
// 1D Depth-Wise Conv (Name: ${nodeName}, Op: ${nodeOp})
3838
BEGIN_SINGLE_CORE
39-
${data_in_type.typeName} ref_${data_out}_${data_in} = ${data_in};
40-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
39+
${data_in_type.typeName} ref_${nodeName}_${data_in} = ${data_in};
40+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
4141
4242
for (uint32_t n=0; n<${batch}; ++n) {
4343
DWConv2d_s${data_in_type.referencedType.typeWidth}_s${weight_type.referencedType.typeWidth}_s${data_out_type.referencedType.typeWidth}_NCHW(
44-
ref_${data_out}_${data_in}, ${ch_im_in}, 1, ${dim_im_in_y},
44+
ref_${nodeName}_${data_in}, ${ch_im_in}, 1, ${dim_im_in_y},
4545
${weight}, 1, ${dim_kernel_y},
4646
1, ${stride_y},
47-
ref_${data_out}_${data_out}, ${input_offset}, ${output_offset}
47+
ref_${nodeName}_${data_out}, ${input_offset}, ${output_offset}
4848
);
49-
ref_${data_out}_${data_in} += ${batchOffsetIn};
50-
ref_${data_out}_${data_out} += ${batchOffsetOut};
49+
ref_${nodeName}_${data_in} += ${batchOffsetIn};
50+
ref_${nodeName}_${data_out} += ${batchOffsetOut};
5151
}
5252
END_SINGLE_CORE
5353
""")
@@ -60,18 +60,18 @@ def alignToContext(self, ctxt: NetworkContext,
6060
6161
// 2D Depth-Wise Conv (Name: ${nodeName}, Op: ${nodeOp})
6262
BEGIN_SINGLE_CORE
63-
${data_in_type.typeName} ref_${data_out}_${data_in} = ${data_in};
64-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
63+
${data_in_type.typeName} ref_${nodeName}_${data_in} = ${data_in};
64+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
6565
6666
for (uint32_t n=0; n<${batch}; ++n) {
6767
DWConv2d_s${data_in_type.referencedType.typeWidth}_s${weight_type.referencedType.typeWidth}_s${data_out_type.referencedType.typeWidth}_NCHW(
68-
ref_${data_out}_${data_in}, ${ch_im_in}, ${dim_im_in_x}, ${dim_im_in_y},
68+
ref_${nodeName}_${data_in}, ${ch_im_in}, ${dim_im_in_x}, ${dim_im_in_y},
6969
${weight}, ${dim_kernel_x}, ${dim_kernel_y},
7070
${stride_x}, ${stride_y},
71-
ref_${data_out}_${data_out}, ${input_offset}, ${output_offset}
71+
ref_${nodeName}_${data_out}, ${input_offset}, ${output_offset}
7272
);
73-
ref_${data_out}_${data_in} += ${batchOffsetIn};
74-
ref_${data_out}_${data_out} += ${batchOffsetOut};
73+
ref_${nodeName}_${data_in} += ${batchOffsetIn};
74+
ref_${nodeName}_${data_out} += ${batchOffsetOut};
7575
}
7676
END_SINGLE_CORE
7777
""")

‎Deeploy/Targets/Generic/Templates/FloatConvTemplate.py‎

Lines changed: 12 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -12,20 +12,20 @@
1212
1313
// 2D FP Conv (Name: ${nodeName}, Op: ${nodeOp})
1414
BEGIN_SINGLE_CORE
15-
${data_in_type.typeName} ref_${data_out}_${data_in} = ${data_in};
16-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
15+
${data_in_type.typeName} ref_${nodeName}_${data_in} = ${data_in};
16+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
1717
1818
for (uint32_t n=0; n<${batch}; ++n) {
1919
Conv2d_fp${data_in_type.referencedType.typeWidth}_fp${weight_type.referencedType.typeWidth}_fp${data_out_type.referencedType.typeWidth}_NCHW(
20-
ref_${data_out}_${data_in}, ${ch_im_in}, ${dim_im_in_x}, ${dim_im_in_y},
20+
ref_${nodeName}_${data_in}, ${ch_im_in}, ${dim_im_in_x}, ${dim_im_in_y},
2121
${weight}, ${ch_im_out}, ${dim_kernel_x}, ${dim_kernel_y},
2222
${stride_x}, ${stride_y},
2323
${bias},
2424
${has_bias},
25-
ref_${data_out}_${data_out}
25+
ref_${nodeName}_${data_out}
2626
);
27-
ref_${data_out}_${data_in} += ${batchOffsetIn};
28-
ref_${data_out}_${data_out} += ${batchOffsetOut};
27+
ref_${nodeName}_${data_in} += ${batchOffsetIn};
28+
ref_${nodeName}_${data_out} += ${batchOffsetOut};
2929
}
3030
END_SINGLE_CORE
3131
""")
@@ -37,21 +37,21 @@
3737
%>
3838
// 1D FP Conv (Name: ${nodeName}, Op: ${nodeOp})
3939
BEGIN_SINGLE_CORE
40-
${data_in_type.typeName} ref_${data_out}_${data_in} = ${data_in};
41-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
40+
${data_in_type.typeName} ref_${nodeName}_${data_in} = ${data_in};
41+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
4242
for (uint32_t n=0; n<${batch}; ++n) {
4343
Conv1d_fp${data_in_type.referencedType.typeWidth}_fp${weight_type.referencedType.typeWidth}_fp${data_out_type.referencedType.typeWidth}(
44-
ref_${data_out}_${data_in}, ${ch_im_in}, ${dim_im_in_y},
44+
ref_${nodeName}_${data_in}, ${ch_im_in}, ${dim_im_in_y},
4545
${weight}, ${ch_im_out}, ${dim_kernel_y},
4646
${stride_y},
4747
${bias},
4848
${has_bias},
49-
ref_${data_out}_${data_out},
49+
ref_${nodeName}_${data_out},
5050
${dim_im_out_y}
5151
);
5252
53-
ref_${data_out}_${data_in} += ${batchOffsetIn};
54-
ref_${data_out}_${data_out} += ${batchOffsetOut};
53+
ref_${nodeName}_${data_in} += ${batchOffsetIn};
54+
ref_${nodeName}_${data_out} += ${batchOffsetOut};
5555
}
5656
END_SINGLE_CORE
5757
""")

‎Deeploy/Targets/Generic/Templates/FloatDWConvTemplate.py‎

Lines changed: 6 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -11,21 +11,21 @@
1111
%>
1212
// 2D FP Depth-wise Conv (Name: ${nodeName}, Op: ${nodeOp})
1313
BEGIN_SINGLE_CORE
14-
${data_in_type.typeName} ref_${data_out}_${data_in} = ${data_in};
15-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
14+
${data_in_type.typeName} ref_${nodeName}_${data_in} = ${data_in};
15+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
1616
for (uint32_t n=0; n<${batch}; ++n) {
1717
DWConv2d_fp${data_in_type.referencedType.typeWidth}_fp${weight_type.referencedType.typeWidth}_fp${data_out_type.referencedType.typeWidth}_NCHW(
18-
ref_${data_out}_${data_in},
18+
ref_${nodeName}_${data_in},
1919
${ch_im_in}, ${dim_im_in_x}, ${dim_im_in_y},
2020
${weight},
2121
${ch_im_out}, ${dim_kernel_x}, ${dim_kernel_y},
2222
${stride_x}, ${stride_y},
2323
${bias},
2424
${has_bias},
25-
ref_${data_out}_${data_out}
25+
ref_${nodeName}_${data_out}
2626
);
27-
ref_${data_out}_${data_in} += ${batchOffsetIn};
28-
ref_${data_out}_${data_out} += ${batchOffsetOut};
27+
ref_${nodeName}_${data_in} += ${batchOffsetIn};
28+
ref_${nodeName}_${data_out} += ${batchOffsetOut};
2929
}
3030
END_SINGLE_CORE
3131
""")

‎Deeploy/Targets/Generic/Templates/FloatMatMulTemplate.py‎

Lines changed: 9 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -7,23 +7,23 @@
77
referenceTemplate = NodeTemplate("""
88
// Matmul (Name: ${nodeName}, Op: ${nodeOp})
99
BEGIN_SINGLE_CORE
10-
${A_type.typeName} ref_${data_out}_${A} = ${A};
11-
${B_type.typeName} ref_${data_out}_${B} = ${B};
12-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
10+
${A_type.typeName} ref_${nodeName}_${A} = ${A};
11+
${B_type.typeName} ref_${nodeName}_${B} = ${B};
12+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
1313
1414
for(uint32_t i=0; i<${batch}; i++){
1515
MatMul_fp${A_type.referencedType.typeWidth}_fp${B_type.referencedType.typeWidth}_fp${data_out_type.referencedType.typeWidth}(
16-
ref_${data_out}_${A},
17-
ref_${data_out}_${B},
18-
ref_${data_out}_${data_out},
16+
ref_${nodeName}_${A},
17+
ref_${nodeName}_${B},
18+
ref_${nodeName}_${data_out},
1919
${M},
2020
${N},
2121
${O}
2222
);
2323
24-
ref_${data_out}_${A} += ${M} * ${N};
25-
ref_${data_out}_${B} += ${N} * ${O};
26-
ref_${data_out}_${data_out} += ${M} * ${O};
24+
ref_${nodeName}_${A} += ${M} * ${N};
25+
ref_${nodeName}_${B} += ${N} * ${O};
26+
ref_${nodeName}_${data_out} += ${M} * ${O};
2727
}
2828
END_SINGLE_CORE
2929
""")

‎Deeploy/Targets/Generic/Templates/FloatMaxPoolTemplate.py‎

Lines changed: 10 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -8,13 +8,13 @@
88
99
// 2D Float MaxPool (Name: ${nodeName}, Op: ${nodeOp})
1010
BEGIN_SINGLE_CORE
11-
${data_in_type.typeName} ref_${data_out}_${data_in} = ${data_in};
12-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
11+
${data_in_type.typeName} ref_${nodeName}_${data_in} = ${data_in};
12+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
1313
1414
for (uint32_t n=0; n<${batch}; ++n) {
1515
MaxPool2d_fp${data_in_type.referencedType.typeWidth}_fp${data_out_type.referencedType.typeWidth}_NCHW(
16-
ref_${data_out}_${data_in}, ${ch_im_in}, ${dim_im_in_x}, ${dim_im_in_y},${dim_kernel_x}, ${dim_kernel_y}, ${stride_x}, ${stride_y},
17-
ref_${data_out}_${data_out}
16+
ref_${nodeName}_${data_in}, ${ch_im_in}, ${dim_im_in_x}, ${dim_im_in_y},${dim_kernel_x}, ${dim_kernel_y}, ${stride_x}, ${stride_y},
17+
ref_${nodeName}_${data_out}
1818
);
1919
2020
}
@@ -28,16 +28,16 @@
2828
%>
2929
// 1D Float MaxPool (Name: ${nodeName}, Op: ${nodeOp})
3030
BEGIN_SINGLE_CORE
31-
${data_in_type.typeName} ref_${data_out}_${data_in} = ${data_in};
32-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
31+
${data_in_type.typeName} ref_${nodeName}_${data_in} = ${data_in};
32+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
3333
for (uint32_t n=0; n<${batch}; ++n) {
3434
MaxPool1d_fp32_fp32(
35-
ref_${data_out}_${data_in}, ${ch_im_in}, ${dim_im_in_y},
35+
ref_${nodeName}_${data_in}, ${ch_im_in}, ${dim_im_in_y},
3636
${dim_kernel_y}, ${stride_y},
37-
ref_${data_out}_${data_out}
37+
ref_${nodeName}_${data_out}
3838
);
39-
ref_${data_out}_${data_in} += ${batchOffsetIn};
40-
ref_${data_out}_${data_out} += ${batchOffsetOut};
39+
ref_${nodeName}_${data_in} += ${batchOffsetIn};
40+
ref_${nodeName}_${data_out} += ${batchOffsetOut};
4141
}
4242
END_SINGLE_CORE
4343
""")

‎Deeploy/Targets/Generic/Templates/MatMulTemplate.py‎

Lines changed: 9 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -34,24 +34,24 @@ def alignToContext(self, ctxt: NetworkContext,
3434
referenceTemplate = _MatMulTemplate("""
3535
// MatMul (Name: ${nodeName}, Op: ${nodeOp})
3636
BEGIN_SINGLE_CORE
37-
${A_type.typeName} ref_${data_out}_${A} = ${A};
38-
${B_type.typeName} ref_${data_out}_${B} = ${B};
39-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
37+
${A_type.typeName} ref_${nodeName}_${A} = ${A};
38+
${B_type.typeName} ref_${nodeName}_${B} = ${B};
39+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
4040
4141
for(uint32_t i=0;i<${batch};i++){
4242
MatMul_s${A_type.referencedType.typeWidth}_s${B_type.referencedType.typeWidth}_s${data_out_type.referencedType.typeWidth}(
43-
ref_${data_out}_${A},
44-
ref_${data_out}_${B},
45-
ref_${data_out}_${data_out},
43+
ref_${nodeName}_${A},
44+
ref_${nodeName}_${B},
45+
ref_${nodeName}_${data_out},
4646
${M},
4747
${N},
4848
${O},
4949
${A_offset}, ${B_offset}, ${C_offset}
5050
);
5151
52-
ref_${data_out}_${A} += ${M} * ${N};
53-
ref_${data_out}_${B} += ${N} * ${O};
54-
ref_${data_out}_${data_out} += ${M} * ${O};
52+
ref_${nodeName}_${A} += ${M} * ${N};
53+
ref_${nodeName}_${B} += ${N} * ${O};
54+
ref_${nodeName}_${data_out} += ${M} * ${O};
5555
}
5656
END_SINGLE_CORE
5757
""")

‎Deeploy/Targets/Generic/Templates/MaxPoolTemplate.py‎

Lines changed: 6 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -36,17 +36,17 @@ def alignToContext(self, ctxt: NetworkContext,
3636
3737
// 2D MaxPool (Name: ${nodeName}, Op: ${nodeOp})
3838
BEGIN_SINGLE_CORE
39-
${data_in_type.typeName} ref_${data_out}_${data_in} = ${data_in};
40-
${data_out_type.typeName} ref_${data_out}_${data_out} = ${data_out};
39+
${data_in_type.typeName} ref_${nodeName}_${data_in} = ${data_in};
40+
${data_out_type.typeName} ref_${nodeName}_${data_out} = ${data_out};
4141
4242
for (uint32_t n=0; n<${batch}; ++n) {
4343
MaxPool2d_s${data_in_type.referencedType.typeWidth}_s${data_out_type.referencedType.typeWidth}_NCHW(
44-
ref_${data_out}_${data_in}, ${ch_im_in}, ${dim_im_in_x}, ${dim_im_in_y},
44+
ref_${nodeName}_${data_in}, ${ch_im_in}, ${dim_im_in_x}, ${dim_im_in_y},
4545
${dim_kernel_x}, ${dim_kernel_y}, ${stride_x}, ${stride_y},
46-
ref_${data_out}_${data_out}, ${input_offset}, ${output_offset}
46+
ref_${nodeName}_${data_out}, ${input_offset}, ${output_offset}
4747
);
48-
ref_${data_out}_${data_in} += ${batchOffsetIn};
49-
ref_${data_out}_${data_out} += ${batchOffsetOut};
48+
ref_${nodeName}_${data_in} += ${batchOffsetIn};
49+
ref_${nodeName}_${data_out} += ${batchOffsetOut};
5050
}
5151
END_SINGLE_CORE
5252
""")

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