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docs/pt/docs/tutorial/security/index.md
### OAuth 1 Havia um OAuth 1, que é bem diferente do OAuth2, e mais complexo, isso incluía diretamente as especificações de como criptografar a comunicação. Não é muito popular ou usado nos dias atuais. OAuth2 não especifica como criptografar a comunicação, ele espera que você tenha sua aplicação em um servidor HTTPS. !!! tip "Dica"
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docs/pt/docs/index.md
<!-- /sponsors --> <a href="https://fastapi.tiangolo.com/pt/fastapi-people/#patrocinadores" class="external-link" target="_blank">Outros patrocinadores</a> ## Opiniões "*[...] Estou usando **FastAPI** muito esses dias. [...] Estou na verdade planejando utilizar ele em todos os times de **serviços _Machine Learning_ na Microsoft**. Alguns deles estão sendo integrados no _core_ do produto **Windows** e alguns produtos **Office**.*"
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tensorflow/c/experimental/gradients/nn_grad_test.cc
A.reset(A_raw); } // Bias float Bias_vals[] = {2.0f, 3.0f}; int64_t Bias_dims[] = {2}; AbstractTensorHandlePtr Bias; { AbstractTensorHandle* Bias_raw; status_ = TestTensorHandleWithDims<float, TF_FLOAT>( immediate_execution_ctx_.get(), Bias_vals, Bias_dims, 1, &Bias_raw); ASSERT_EQ(errors::OK, status_.code()) << status_.message(); Bias.reset(Bias_raw); }
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 8.3K bytes - Viewed (0) -
okhttp/src/main/kotlin/okhttp3/internal/idn/Punycode.kt
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tensorflow/c/experimental/gradients/nn_grad.cc
TF_RETURN_IF_ERROR(forward_attrs_.Get("data_format", &data_format)); // Grad for A grad_inputs[0] = upstream_grad; grad_inputs[0]->Ref(); // Grad for bias std::string name = "bias_add_grad"; TF_RETURN_IF_ERROR(BiasAddGrad(ctx, upstream_grad, &grad_inputs[1], data_format.c_str(), name.c_str())); return absl::OkStatus(); }
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 5.7K bytes - Viewed (0) -
android/guava/src/com/google/common/math/DoubleUtils.java
// The mask for the sign, according to the {@link // Double#doubleToRawLongBits(double)} spec. static final long SIGN_MASK = 0x8000000000000000L; static final int SIGNIFICAND_BITS = 52; static final int EXPONENT_BIAS = 1023; /** The implicit 1 bit that is omitted in significands of normal doubles. */ static final long IMPLICIT_BIT = SIGNIFICAND_MASK + 1; static long getSignificand(double d) {
Java - Registered: Fri Apr 26 12:43:10 GMT 2024 - Last Modified: Wed Apr 28 15:37:52 GMT 2021 - 5.1K bytes - Viewed (0) -
RELEASE.md
* XLA reduction emitter is deterministic when the environment variable `TF_DETERMINISTIC_OPS` is set to "true" or "1". This extends deterministic `tf.nn.bias_add` back-prop functionality (and therefore also deterministic back-prop of bias-addition in Keras layers) to include when XLA JIT compilation is enabled. * Fix problem, when running on a CUDA GPU and when either environment
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android/guava-tests/benchmark/com/google/common/collect/ConcurrentHashMultisetBenchmark.java
Random random = new Random(); int nKeys = keys.size(); long blah = 0; for (int i = 0; i < reps; i++) { Integer key = keys.get(random.nextInt(nKeys)); // This range is [-5, 4] - slight negative bias so we often hit zero, which brings the // auto-removal of zeroes into play. int delta = random.nextInt(10) - 5; blah += delta; if (delta >= 0) { multiset.add(key, delta);
Java - Registered: Fri Apr 26 12:43:10 GMT 2024 - Last Modified: Thu Apr 06 12:56:11 GMT 2023 - 16.6K bytes - Viewed (0) -
android/guava/src/com/google/thirdparty/publicsuffix/PublicSuffixPatterns.java
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Java - Registered: Fri Apr 26 12:43:10 GMT 2024 - Last Modified: Thu Mar 21 21:04:43 GMT 2024 - 72.4K bytes - Viewed (1) -
doc/go1.17_spec.html
advances. </p> <pre> RowLoop: for y, row := range rows { for x, data := range row { if data == endOfRow { continue RowLoop } row[x] = data + bias(x, y) } } </pre> <h3 id="Goto_statements">Goto statements</h3> <p> A "goto" statement transfers control to the statement with the corresponding label within the same function. </p>
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