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Prepare restoration of Tensorflow driver for Core 3 (#21327) 

* Fix compilation of conv.cc

* fix compilation of depthwise_conv.cc
This commit is contained in:
Christian Baars 2024-05-03 12:28:49 +02:00 committed by GitHub
parent 041540c80c
commit 6f20dcd0ed
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GPG Key ID: B5690EEEBB952194
2 changed files with 12 additions and 12 deletions
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12
lib/libesp32_ml/tf_lite_esp32/src/tensorflow/lite/micro/kernels/esp_nn/conv.cc
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@ -115,13 +115,13 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
if (input->type == kTfLiteInt8) {
data_dims_t input_dims = {
.width = input_width, .height = input_height,
.channels = input->dims->data[3], 1
.channels = input->dims->data[3], .extra = 1
};
data_dims_t output_dims = {
.width = output_width, .height = output_height,
.channels = output->dims->data[3], 1
.channels = output->dims->data[3], .extra = 1
};
data_dims_t filter_dims = {.width = filter_width, .height = filter_height, 0, 0};
data_dims_t filter_dims = {.width = filter_width, .height = filter_height, .channels = 0, .extra = 0};
conv_params_t conv_params = {
.in_offset = 0, .out_offset = 0,
.stride = {params.stride_width, params.stride_height},
@ -209,13 +209,13 @@ inline void EvalQuantizedPerChannel(
data_dims_t input_dims = {
.width = input_width, .height = input_height,
.channels = input_depth, 1
.channels = input_depth, .extra = 1
};
data_dims_t output_dims = {
.width = output_width, .height = output_height,
.channels = output_depth, 1
.channels = output_depth, .extra = 1
};
data_dims_t filter_dims = {.width = filter_width, .height = filter_height, 0, 0};
data_dims_t filter_dims = {.width = filter_width, .height = filter_height, .channels = 0, .extra = 0};
conv_params_t conv_params = {
.in_offset = input_offset, .out_offset = output_offset,
.stride = {stride_width, stride_height},

12
lib/libesp32_ml/tf_lite_esp32/src/tensorflow/lite/micro/kernels/esp_nn/depthwise_conv.cc
View File

@ -118,13 +118,13 @@ inline void EvalQuantizedPerChannel(TfLiteContext* context, TfLiteNode* node,
data_dims_t input_dims = {
.width = input_width, .height = input_height,
.channels = input_depth, 1
.channels = input_depth, .extra = 1
};
data_dims_t output_dims = {
.width = output_width, .height = output_height,
.channels = output_depth, 1
.channels = output_depth, .extra = 1
};
data_dims_t filter_dims = {.width = filter_width, .height = filter_height, 0, 0};
data_dims_t filter_dims = {.width = filter_width, .height = filter_height, .channels = 0, .extra = 0};
dw_conv_params_t conv_params = {
.in_offset = input_offset, .out_offset = output_offset,
.ch_mult = depth_multiplier,
@ -227,13 +227,13 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
if (input->type == kTfLiteInt8) {
data_dims_t input_dims = {
.width = input_width, .height = input_height,
.channels = input->dims->data[3], 1
.channels = input->dims->data[3], .extra = 1
};
data_dims_t output_dims = {
.width = output_width, .height = output_height,
.channels = output->dims->data[3], 1
.channels = output->dims->data[3], .extra = 1
};
data_dims_t filter_dims = {.width = filter_width, .height = filter_height, 0, 0};
data_dims_t filter_dims = {.width = filter_width, .height = filter_height, .channels = 0, .extra = 0};
dw_conv_params_t conv_params = {
.in_offset = 0, .out_offset = 0,
.ch_mult = params.depth_multiplier,