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Fixed multiple typos in XNNPACK delegate tensor type checking code

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Some XNNPACK delegate methods intended for visiting nodes (`VisitConv2DNode`, `VisitFullyConnectedNode` and `VisitMediaPipeDeconvolutionNode`) had typos in tensor type checking code, which leaded to double checking of `filter_tensor` type and `bias_tensor` type not being checked at all.
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Georgiy Manuilov 2020-11-22 15:12:17 +03:00 committed by GitHub
parent 2cad9d750c
commit 93001d25d9
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1 changed files with 3 additions and 3 deletions
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tensorflow/lite/delegates/xnnpack/xnnpack_delegate.cc
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@ -1335,7 +1335,7 @@ class Subgraph {
} }
const TfLiteTensor& bias_tensor = tensors[bias_tensor_id]; const TfLiteTensor& bias_tensor = tensors[bias_tensor_id];
TF_LITE_ENSURE_STATUS(CheckTensorFloatType( TF_LITE_ENSURE_STATUS(CheckTensorFloatType(
logging_context, filter_tensor, node->inputs->data[2], node_index)); logging_context, bias_tensor, node->inputs->data[2], node_index));
TF_LITE_ENSURE_STATUS(CheckTensorShape(logging_context, bias_tensor, 1, TF_LITE_ENSURE_STATUS(CheckTensorShape(logging_context, bias_tensor, 1,
node->inputs->data[2])); node->inputs->data[2]));
if (quasi_static_tensors.count(node->inputs->data[2]) == 0) { if (quasi_static_tensors.count(node->inputs->data[2]) == 0) {
@ -1526,7 +1526,7 @@ class Subgraph {
} }
const TfLiteTensor& bias_tensor = tensors[bias_tensor_id]; const TfLiteTensor& bias_tensor = tensors[bias_tensor_id];
TF_LITE_ENSURE_STATUS(CheckTensorFloatType( TF_LITE_ENSURE_STATUS(CheckTensorFloatType(
logging_context, filter_tensor, node->inputs->data[2], node_index)); logging_context, bias_tensor, node->inputs->data[2], node_index));
TF_LITE_ENSURE_STATUS(CheckTensorShape(logging_context, bias_tensor, 1, TF_LITE_ENSURE_STATUS(CheckTensorShape(logging_context, bias_tensor, 1,
node->inputs->data[2])); node->inputs->data[2]));
if (quasi_static_tensors.count(node->inputs->data[2]) == 0) { if (quasi_static_tensors.count(node->inputs->data[2]) == 0) {
@ -1983,7 +1983,7 @@ class Subgraph {
const TfLiteTensor& bias_tensor = tensors[node->inputs->data[2]]; const TfLiteTensor& bias_tensor = tensors[node->inputs->data[2]];
TF_LITE_ENSURE_STATUS(CheckTensorFloatType( TF_LITE_ENSURE_STATUS(CheckTensorFloatType(
logging_context, filter_tensor, node->inputs->data[2], node_index)); logging_context, bias_tensor, node->inputs->data[2], node_index));
TF_LITE_ENSURE_STATUS(CheckTensorShape(logging_context, bias_tensor, 1, TF_LITE_ENSURE_STATUS(CheckTensorShape(logging_context, bias_tensor, 1,
node->inputs->data[2])); node->inputs->data[2]));
if (quasi_static_tensors.count(node->inputs->data[2]) == 0) { if (quasi_static_tensors.count(node->inputs->data[2]) == 0) {