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

  }
}

// 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>.

  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);

### 实时文档

在本地开发时，可以使用该脚本构建站点并检查所做的任何更改，并实时重载：

<div class="termy">

```console
$ python ./scripts/docs.py live

<span style="color: green;">[INFO]</span> Serving on http://127.0.0.1:8008
<span style="color: green;">[INFO]</span> Start watching changes
<span style="color: green;">[INFO]</span> Start detecting changes
```

</div>

文档服务将运行在 `http://127.0.0.1:8008`。

这样，你可以编辑文档 / 源文件并实时查看更改。

!!! tip

    params->emplace_back(handle);
  }
  return absl::OkStatus();
}

// Runs `model` maybe wrapped in a function.
Status RunModel(Model model, AbstractContext* ctx,
                absl::Span<AbstractTensorHandle* const> inputs,
                absl::Span<AbstractTensorHandle*> outputs, bool use_function) {
  if (use_function) {
    const char* fn_name = "test_fn";
    core::RefCountPtr<AbstractFunction> scoped_func;

    @Override
    public void render(String text, SimpleHtmlWriter htmlWriter) throws IOException {
        // Wrap in a <span>, to work around CSS problem in IE
        htmlWriter.startElement("span").attribute("class", "code")
            .startElement("pre").characters(text).endElement()
        .endElement();
    }

    <a class="badge" href="https://dpeuniversity.gradle.com/app/courses/ec69d0b8-9171-4969-ac3e-82dea16f87b0/" target="_blank">
        <span class="badge-type button--blue">LEARN</span>
        <span class="badge-text">Incremental Builds and Build Caching with Gradle&nbsp;&nbsp;&nbsp;&gt;</span>
    </a>
</div>
++++

Gradle uses two main features to reduce build time: *incremental builds* and *build caching*.