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Results 1 - 7 of 7 for size_a (0.29 sec)
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tensorflow/compiler/mlir/lite/quantization/lite/quantize_model_test.cc
ASSERT_THAT(sizeof(float) * weights_buffer->data.size(), Eq(original_weights_buffer->data()->size())); int num_values_in_channel = weights_buffer->data.size() / out_channel_size; for (size_t channel_idx = 0; channel_idx < out_channel_size; channel_idx++) { for (size_t j = 0; j < num_values_in_channel; j++) { size_t element_idx = channel_idx * out_channel_size + j;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 73.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/string_utils.cc
memcpy(*buffer, &num_strings, sizeof(int32_t)); // Set offset of strings. int32_t start = sizeof(int32_t) * (num_strings + 2); for (size_t i = 0; i < offset_.size(); i++) { // TODO(b/165919229): This code will need changing if/when we port to a // big-endian platform. int32_t offset = start + offset_[i]; memcpy(*buffer + sizeof(int32_t) * (i + 1), &offset, sizeof(int32_t)); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:41:49 UTC 2024 - 2.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/string_utils.h
std::vector<size_t> offset_; // Max length in number of characters that we permit the total // buffer containing the concatenation of all added strings to be. // For historical reasons this is limited to 32bit length. At this files // inception, sizes were represented using 32bit which forced an implicit cap // on the size of the buffer. When this was refactored to use size_t (which
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:41:49 UTC 2024 - 2.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights_test.cc
ASSERT_TRUE(output_model); ASSERT_EQ(output_model->subgraphs()->size(), model_->subgraphs()->size()); uint32_t num_conv_ops = 0; for (size_t subgraph_idx = 0; subgraph_idx < model_->subgraphs()->size(); ++subgraph_idx) { const auto quantized_graph = output_model->subgraphs()->Get(subgraph_idx); for (size_t i = 0; i < quantized_graph->operators()->size(); ++i) { const auto op = quantized_graph->operators()->Get(i);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 32.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/flatbuffer_export.cc
<< ") != terminator operands (" << term->getNumOperands() << ")"; return {}; } // Verify number of tensors for inputs and outputs matches size // of the list in the signature def. if (input_names.size() != sig_def_inputs.size() || output_names.size() != sig_def_outputs.size()) { main_op.emitWarning(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:41:49 UTC 2024 - 164.5K bytes - Viewed (2) -
cmd/xl-storage.go
return sizeSummary{}, errSkipFile } sizeS := sizeSummary{} for _, tier := range globalTierConfigMgr.ListTiers() { if sizeS.tiers == nil { sizeS.tiers = make(map[string]tierStats) } sizeS.tiers[tier.Name] = tierStats{} } if sizeS.tiers != nil { sizeS.tiers[storageclass.STANDARD] = tierStats{} sizeS.tiers[storageclass.RRS] = tierStats{} }
Registered: Sun Jun 16 00:44:34 UTC 2024 - Last Modified: Mon Jun 10 15:51:27 UTC 2024 - 85.3K bytes - Viewed (2) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc
tensorflow::TensorShape ToTensorShape(llvm::ArrayRef<T> sizes) { return tensorflow::TensorShape( llvm::SmallVector<int64_t, num_dims>(sizes.begin(), sizes.end())); } template <typename T, int num_dims> tensorflow::TensorShape ToTensorShape( llvm::iterator_range<DenseElementsAttr::ElementIterator<T>> sizes) { return tensorflow::TensorShape( llvm::SmallVector<int64_t, num_dims>(sizes.begin(), sizes.end())); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (1)