feat(compression): implement tensor decompression in op depthwise conv

Implement tensor decompression in op depthwise conv. Extend tests
to validate operation on compressed tensors.

BUG=part of #2636

tensorflow/lite/micro/kernels/depthwise_conv.cc

@@ -1,4 +1,4 @@
-/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -52,16 +52,37 @@ TfLiteStatus DepthwiseConvEval(TfLiteContext* context, TfLiteNode* node) {
           ? tflite::micro::GetEvalInput(context, node, kDepthwiseConvBiasTensor)
           : nullptr;
 
+#ifdef USE_TFLM_COMPRESSION
+
+  MicroContext* micro_context = GetMicroContext(context);
+
+  const CompressionTensorData* filter_comp_td =
+      micro_context->GetTensorCompressionData(node,
+                                              kDepthwiseConvWeightsTensor);
+  const CompressionTensorData* bias_comp_td =
+      micro_context->GetTensorCompressionData(node, kDepthwiseConvBiasTensor);
+
+#endif  // USE_TFLM_COMPRESSION
+
   switch (input->type) {  // Already know in/out types are same.
     case kTfLiteFloat32: {
       tflite::reference_ops::DepthwiseConv(
           DepthwiseConvParamsFloat(params, data),
           tflite::micro::GetTensorShape(input),
           tflite::micro::GetTensorData<float>(input),
           tflite::micro::GetTensorShape(filter),
+#ifdef USE_TFLM_COMPRESSION
+          tflite::micro::GetTensorData<float>(micro_context, filter,
+                                              filter_comp_td,
+                                              data.weights_scratch_index),
+          tflite::micro::GetTensorShape(bias),
+          tflite::micro::GetTensorData<float>(micro_context, bias, bias_comp_td,
+                                              data.bias_scratch_index),
+#else   // USE_TFLM_COMPRESSION
           tflite::micro::GetTensorData<float>(filter),
           tflite::micro::GetTensorShape(bias),
           tflite::micro::GetOptionalTensorData<float>(bias),
+#endif  // USE_TFLM_COMPRESSION
           tflite::micro::GetTensorShape(output),
           tflite::micro::GetTensorData<float>(output));
       break;
@@ -94,9 +115,18 @@ TfLiteStatus DepthwiseConvEval(TfLiteContext* context, TfLiteNode* node) {
               tflite::micro::GetTensorShape(input),
               tflite::micro::GetTensorData<int8_t>(input),
               tflite::micro::GetTensorShape(filter),
+#ifdef USE_TFLM_COMPRESSION
+              tflite::micro::GetTensorData<int8_t>(micro_context, filter,
+                                                   filter_comp_td,
+                                                   data.weights_scratch_index),
+              tflite::micro::GetTensorShape(bias),
+              tflite::micro::GetTensorData<int32_t>(
+                  micro_context, bias, bias_comp_td, data.bias_scratch_index),
+#else   // USE_TFLM_COMPRESSION
               tflite::micro::GetTensorData<int8_t>(filter),
               tflite::micro::GetTensorShape(bias),
               tflite::micro::GetOptionalTensorData<int32_t>(bias),
+#endif  // USE_TFLM_COMPRESSION
               tflite::micro::GetTensorShape(output),
               tflite::micro::GetTensorData<int8_t>(output));
           break;
@@ -118,9 +148,18 @@ TfLiteStatus DepthwiseConvEval(TfLiteContext* context, TfLiteNode* node) {
               tflite::micro::GetTensorShape(input),
               tflite::micro::GetTensorData<int16_t>(input),
               tflite::micro::GetTensorShape(filter),
+#ifdef USE_TFLM_COMPRESSION
+              tflite::micro::GetTensorData<int8_t>(micro_context, filter,
+                                                   filter_comp_td,
+                                                   data.weights_scratch_index),
+              tflite::micro::GetTensorShape(bias),
+              tflite::micro::GetTensorData<int64_t>(
+                  micro_context, bias, bias_comp_td, data.bias_scratch_index),
+#else   // USE_TFLM_COMPRESSION
               tflite::micro::GetTensorData<int8_t>(filter),
               tflite::micro::GetTensorShape(bias),
               tflite::micro::GetOptionalTensorData<int64_t>(bias),
+#endif  // USE_TFLM_COMPRESSION
               tflite::micro::GetTensorShape(output),
               tflite::micro::GetTensorData<int16_t>(output));
           break;

tensorflow/lite/micro/kernels/depthwise_conv_common.cc

@@ -1,4 +1,4 @@
-/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2024 The TensorFlow Authors. All Rights Reserved.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -127,7 +127,9 @@ TfLiteStatus CalculateOpDataDepthwiseConv(
 
   micro_context->DeallocateTempTfLiteTensor(input);
   micro_context->DeallocateTempTfLiteTensor(filter);
-  micro_context->DeallocateTempTfLiteTensor(bias);
+  if (has_bias) {
+    micro_context->DeallocateTempTfLiteTensor(bias);
+  }
   micro_context->DeallocateTempTfLiteTensor(output);
 
   return kTfLiteOk;
@@ -209,6 +211,23 @@ TfLiteStatus DepthwiseConvPrepare(TfLiteContext* context, TfLiteNode* node) {
       context, node, params, input_width, input_height, filter_width,
       filter_height, output_width, output_height, input->type, data));
 
+#ifdef USE_TFLM_COMPRESSION
+
+  // Compression scratch buffers.
+  // These will only be allocated if the tensor is compressed.
+  if (micro_context->IsTensorCompressed(node, kDepthwiseConvWeightsTensor) &&
+      filter->type == kTfLiteInt4) {
+    MicroPrintf("Compression not supported with INT4 tensors");
+    return kTfLiteError;
+  }
+  data->weights_scratch_index =
+      micro_context->AllocateDecompressionScratchBuffer(
+          node, kDepthwiseConvWeightsTensor);
+  data->bias_scratch_index = micro_context->AllocateDecompressionScratchBuffer(
+      node, kDepthwiseConvBiasTensor);
+
+#endif  // USE_TFLM_COMPRESSION
+
   micro_context->DeallocateTempTfLiteTensor(output);
   micro_context->DeallocateTempTfLiteTensor(input);
   micro_context->DeallocateTempTfLiteTensor(filter);