Puedes utilizar esta plantilla para comenzar, ya que incluye gran parte de la configuración inicial, seguridad, base de datos y algunos endpoints de API ya realizados.

Repositorio en GitHub: [Full Stack FastAPI Template](https://github.com/tiangolo/full-stack-fastapi-template)

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/unified_api_testutil.h"

namespace tensorflow {
namespace gradients {

/* Returns numerical grad inside `dtheta_approx` given `forward` model and
 * parameter specified by `input_index`.
 *
 * I.e. if y = <output of the forward model> and w = inputs[input_index],
 * this will calculate dy/dw numerically.
 *

        "unigram_tokenizer": {
          "type": "ngram",
          "min_gram": 1,
          "max_gram": 1,
          "token_chars": []
        },
        "unigram_search_tokenizer": {
          "type": "ngram",
          "min_gram": 1,
          "max_gram": 1,
          "token_chars": []
        },
        "bigram_tokenizer": {
          "type": "ngram",
          "min_gram": 2,
          "max_gram": 2,

      } finally {
        monitor.leave();
      }
    } else {
      // It is possible due to races that we are currently in the expected state even though we
      // timed out. e.g. if we weren't event able to grab the lock within the timeout we would never
      // even check the guard. I don't think we care too much about this use case but it could lead
      // to a confusing error message.

// Adds a copy of function `func` and optionally its gradient function `grad`
// to `g`. Once `func`/`grad` is added to `g`, it can be called by creating
// an operation using the function's name.
// Any changes to `func`/`grad` (including deleting it) done after this method
// returns, won't affect the copy of `func`/`grad` in `g`.
// If `func` or `grad` are already in `g`, TF_GraphCopyFunction has no

        with:
          registry: us-central1-docker.pkg.dev
          username: _json_key
          password: ${{ secrets.GCP_CREDS }}
      -
        name: Grab the upcoming TF version to tag this container
        run: |
          # [[:digit:]] searches for numbers and \+ joins them together

pkg debug/elf, method (*File) DynamicSymbols() ([]Symbol, error)
pkg debug/elf, var ErrNoSymbols error

# CL 106460044 debug/plan9obj, cmd/addr2line: on Plan 9 use a.out header, Aram Hăvărneanu <aram@mgk.ro>
pkg debug/plan9obj, type FileHeader struct, HdrSize uint64
pkg debug/plan9obj, type FileHeader struct, LoadAddress uint64

    `RandomTranslation`, `RandomRotation`, `RandomHeight`, `RandomWidth`,
    `RandomZoom`, `RandomContrast`
*   Improved **`TextVectorization`** layer, which handles string tokenization,
    n-gram generation, and token encoding
    *   The `TextVectorization` layer now accounts for the mask_token as part of
        the vocabulary size when output_mode='int'. This means that, if you have

        with:
          registry: us-central1-docker.pkg.dev
          username: _json_key
          password: ${{ secrets.GCP_CREDS }}
      -
        name: Grab the date to do cache busting (assumes same day OK to keep)
        run: |
          echo "DATE=$(date +'%Y-%m-%d')" >> "$GITHUB_OUTPUT"
        id: date
      -

そして複数のプロセスは通常、**メモリを共有しません**。これは、実行中の各プロセスがそれぞれ独自の変数やメモリ等を持っていることを意味します。つまり、コード内で大量のメモリを消費している場合、**各プロセス**は同等の量のメモリを消費することになります。

### サーバーメモリー

例えば、あなたのコードが **1GBのサイズの機械学習モデル**をロードする場合、APIで1つのプロセスを実行すると、少なくとも1GBのRAMを消費します。

また、**4つのプロセス**（4つのワーカー）を起動すると、それぞれが1GBのRAMを消費します。つまり、合計でAPIは**4GBのRAM**を消費することになります。

リモートサーバーや仮想マシンのRAMが3GBしかない場合、4GB以上のRAMをロードしようとすると問題が発生します。🚨