aria-label="Close">
                                                    <span aria-hidden="true">×</span>
                                                </button>
                                            </div>
                                            <div class="modal-body">

string ArgTypeView::TypeName() const {
  if (arg_type_.is_read_only()) {
    if (arg_type_.is_list()) {
      return "absl::Span<AbstractTensorHandle* const>";
    } else {
      return "AbstractTensorHandle* const";
    }
  } else {
    if (arg_type_.is_list()) {
      return "absl::Span<AbstractTensorHandle*>";
    } else {
      return "AbstractTensorHandle**";
    }
  }
}

}  // namespace cpp

package main

import "unsafe"

func main() {
	// Construct an invalid pointer.  We do this by
	// making a pointer which points to the unused space
	// between the last 48-byte object in a span and the
	// end of the span (there are 32 unused bytes there).
	p := new([48]byte)              // make a 48-byte object
	sink = &p                       // escape it, so it allocates for real
	u := uintptr(unsafe.Pointer(p)) // get its address

#define TENSORFLOW_COMPILER_MLIR_QUANTIZATION_TENSORFLOW_CALIBRATOR_CALIBRATION_STATISTICS_COLLECTOR_BASE_H_

#include <cstdint>
#include <optional>

#include "absl/types/span.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics.pb.h"

namespace tensorflow {
namespace calibrator {

// Abstract base class for CalibrationStatisticsCollcetor such as

}

div.tab td:first-child {
    padding-left: 0;
}

div.tab td.numeric, div.tab th.numeric {
    text-align: right;
}

span.code {
    display: inline-block;
    margin-top: 0em;
    margin-bottom: 1em;
}

span.code pre {
    font-size: 11pt;
    padding-top: 10px;
    padding-bottom: 10px;
    padding-left: 10px;
    padding-right: 10px;
    margin: 0;

            new ListSerializer<StyledTextOutputEvent.Span>(
                new SpanSerializer(serializerFactory.getSerializerFor(StyledTextOutput.Style.class))))
    }

    def "can serialize StyledTextOutputEvent messages"() {
        given:
        List spans = [new StyledTextOutputEvent.Span(StyledTextOutput.Style.Description, "description"),
                      new StyledTextOutputEvent.Span(StyledTextOutput.Style.Error, "error")]

  std::optional<AttrKeyValuePair> attr_;
};

::testing::Matcher<const Node*> NodeWith(
    absl::Span<const NodeMatcherProperties> props);

impl::NodeMatcherProperties Inputs(
    absl::Span<const ::testing::Matcher<OutEdge>> inputs);

impl::NodeMatcherProperties CtrlDeps(
    absl::Span<const ::testing::Matcher<const Node*>> control_deps);

impl::NodeMatcherProperties Attr(std::pair<string, AttrValue> attrs);

  Status ComputeGradient(
      const VSpace<Gradient, BackwardFunction, TapeTensor>& vspace,
      const absl::Span<const int64_t> target_tensor_ids,
      const absl::Span<const int64_t> source_tensor_ids,
      const std::unordered_map<int64, TapeTensor>& sources_that_are_targets,
      gtl::ArraySlice<Gradient*> output_gradients, absl::Span<Gradient*> result,
      bool build_default_zeros_grads = true);

  }
}

// Runs model as is if output is a scalar,
// else sums the output tensor before returning.
Status RunAndMaybeSum(AbstractContext* ctx, Model forward,
                      absl::Span<AbstractTensorHandle* const> inputs,
                      absl::Span<AbstractTensorHandle*> outputs,
                      bool use_function) {
  AbstractTensorHandle* model_outputs[1];

  // Run the model.
  TF_RETURN_IF_ERROR(

```

👆 💪 📨 & 📨 💱, ✍, & 🎻 💽.

## 🔄 ⚫️

🚥 👆 📁 📛 `main.py`, 🏃 👆 🈸 ⏮️:

<div class="termy">

```console
$ uvicorn main:app --reload

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

</div>

📂 👆 🖥 <a href="http://127.0.0.1:8000" class="external-link" target="_blank">http://127.0.0.1:8000</a>.