// The default NumPy-style output can be distractingly long in error
    // messages.
    value_string = absl::StrCat(value_string.substr(0, 100), " [...]");
  }
  absl::Status s;
  const char* device_name = DeviceName(&s);
  if (!s.ok()) {
    device_name = "<error fetching device name>";
  }
  return absl::StrCat("TensorHandle(", value_string, ", shape=", shape_string,

#ifndef TENSORFLOW_C_EAGER_IMMEDIATE_EXECUTION_OPERATION_H_
#define TENSORFLOW_C_EAGER_IMMEDIATE_EXECUTION_OPERATION_H_

#include <memory>

#include "absl/types/optional.h"
#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_operation.h"
#include "tensorflow/c/eager/immediate_execution_tensor_handle.h"
#include "tensorflow/c/tensor_interface.h"

Coitados dos banners de cookies com todo o seu esforço para obter o seu consentimento para a <abbr title="Isso é uma outra piada. Não preste atenção em mim. Beba um café com o seu cookie. ☕">API rejeitá-lo</abbr>. 🍪

* <a href="https://github.com/OAI/OpenAPI-Specification" class="external-link" target="_blank"><strong>OpenAPI</strong></a> для создания API, включая объявления <abbr title="также известных, как  HTTP-методы, такие, как: POST, GET, PUT, DELETE">операций</abbr> <abbr title="известные как: эндпоинты, маршруты, 'ручки' и т.п.">пути</abbr>, параметров, тела запроса, безопасности и т.д.

    out_dims[i] = TF_Dim(t, i);
  }
}

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

## 🔢 🔬: 🎈, 🌘 🌘 & 🌘 🌘

🔢 🔬 👷 `float` 💲.

📥 🌐❔ ⚫️ ▶️️ ⚠ 💪 📣 <abbr title="greater than"><code>gt</code></abbr> &amp; 🚫 <abbr title="greater than or equal"><code>ge</code></abbr>. ⏮️ ⚫️ 👆 💪 🚚, 🖼, 👈 💲 🔜 👑 🌘 `0`, 🚥 ⚫️ 🌘 🌘 `1`.

, `0.5` 🔜 ☑ 💲. ✋️ `0.0` ⚖️ `0` 🔜 🚫.

&amp; 🎏 <abbr title="less than"><code>lt</code></abbr>.

```Python hl_lines="11"

	in, arg, out string
}

var trimTests = []TrimTest{
	{"Trim", "abba", "a", "bb"},
	{"Trim", "abba", "ab", ""},
	{"TrimLeft", "abba", "ab", ""},
	{"TrimRight", "abba", "ab", ""},
	{"TrimLeft", "abba", "a", "bba"},
	{"TrimLeft", "abba", "b", "abba"},
	{"TrimRight", "abba", "a", "abb"},
	{"TrimRight", "abba", "b", "abba"},
	{"Trim", "<tag>", "<>", "tag"},
	{"Trim", "* listitem", " *", "listitem"},

    return absl::OkStatus();
  }
  absl::Status SetAttrFloat(const char* attr_name, float value) override {
    op_->node_builder.Attr(attr_name, value);
    return absl::OkStatus();
  }
  absl::Status SetAttrBool(const char* attr_name, bool value) override {
    op_->node_builder.Attr(attr_name, value);
    return absl::OkStatus();
  }
  absl::Status SetAttrType(const char* const attr_name,

{!../../docs_src/path_params/tutorial002.py!}
```

👉 💼, `item_id` 📣 `int`.

/// check

👉 🔜 🤝 👆 👨‍🎨 🐕‍🦺 🔘 👆 🔢, ⏮️ ❌ ✅, 🛠️, ♒️.

///

## 💽 <abbr title="also known as: serialization, parsing, marshalling">🛠️</abbr>

🚥 👆 🏃 👉 🖼 &amp; 📂 👆 🖥 <a href="http://127.0.0.1:8000/items/3" class="external-link" target="_blank">http://127.0.0.1:8000/items/3</a>, 👆 🔜 👀 📨:

```JSON
{"item_id":3}
```

        absl::StrCat("ZerosLike", ToId(t)).c_str()));
  }
  TF_RETURN_IF_ERROR(op->AddInput(t));
  int num_outputs = 1;
  std::vector<AbstractTensorHandle*> outputs(num_outputs);
  TF_RETURN_IF_ERROR(
      op->Execute(absl::Span<AbstractTensorHandle*>(outputs), &num_outputs));
  *result = outputs[0];
  return absl::OkStatus();
}
}  // namespace

absl::Status GradientRegistry::Register(