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  2. github.com/tensorflow/tensorflow

    tensorflow/c/eager/c_api_distributed_test.cc 

      TFE_DeleteContextOptions(opts);

  TFE_ContextSetServerDef(ctx, 0, serialized.data(), serialized.size(), status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Use large matrices so that RPCs don't return before we get a chance
  // to call TFE_DeleteContext.
  TFE_TensorHandle* h0_task0 = TestMatrixTensorHandle100x100(ctx);
  TFE_TensorHandle* h1_task0 = TestMatrixTensorHandle100x100(ctx);
    Created: Tue Apr 07 12:39:13 GMT 2026
    - Last Modified: Sat Oct 12 05:11:17 GMT 2024
    - 23.4K bytes
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  3. github.com/tiangolo/fastapi

    docs/pt/docs/async.md 

    * **Aprendizado de Máquina**: Normalmente exige muita multiplicação de matrizes e vetores. Pense numa grande planilha com números e em multiplicar todos eles juntos e ao mesmo tempo.
    Created: Sun Apr 05 07:19:11 GMT 2026
    - Last Modified: Thu Mar 19 18:20:43 GMT 2026
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  4. github.com/tiangolo/fastapi

    docs/fr/docs/async.md 

    * L'apprentissage automatique (ou **Machine Learning**) : cela nécessite de nombreuses multiplications de matrices et vecteurs. Imaginez une énorme feuille de calcul remplie de nombres que vous multiplierez entre eux tous au même moment.
    Created: Sun Apr 05 07:19:11 GMT 2026
    - Last Modified: Thu Mar 19 18:37:13 GMT 2026
    - 27.3K bytes
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