- Sort Score
- Result 10 results
- Languages All
Results 1 - 10 of 10 for mateixes (0.28 sec)
-
src/main/resources/fess_indices/fess/ca/stopwords.txt
fora gairebé ha han has havia he hem heu hi ho i igual iguals ja l'hi la les li li'n llavors m'he ma mal malgrat mateix mateixa mateixes mateixos me mentre més meu meus meva meves molt molta moltes molts mon mons n'he n'hi ne ni no nogensmenys només nosaltres
Plain Text - Registered: Mon Apr 22 08:04:10 GMT 2024 - Last Modified: Thu Jul 19 06:31:02 GMT 2018 - 1.3K bytes - Viewed (0) -
src/main/resources/fess_indices/_aws/fess.json
"estàveu", "esteu", "et", "etc", "ets", "fins", "fora", "gairebé", "ha", "han", "has", "havia", "he", "hem", "heu", "hi ", "ho", "i", "igual", "iguals", "ja", "l'hi", "la", "les", "li", "li'n", "llavors", "m'he", "ma", "mal", "malgrat", "mateix", "mateixa", "mateixes", "mateixos", "me", "mentre", "més", "meu", "meus", "meva", "meves", "molt", "molta", "moltes", "molts", "mon", "mons", "n'he", "n'hi", "ne", "ni", "no", "nogensmenys", "només", "nosaltres", "nostra", "nostre", "nostres", "o", "oh", "oi", "on",...
Json - Registered: Mon Apr 22 08:04:10 GMT 2024 - Last Modified: Tue Mar 23 12:38:28 GMT 2021 - 117.3K bytes - Viewed (0) -
src/main/resources/fess_indices/_cloud/fess.json
"estàveu", "esteu", "et", "etc", "ets", "fins", "fora", "gairebé", "ha", "han", "has", "havia", "he", "hem", "heu", "hi ", "ho", "i", "igual", "iguals", "ja", "l'hi", "la", "les", "li", "li'n", "llavors", "m'he", "ma", "mal", "malgrat", "mateix", "mateixa", "mateixes", "mateixos", "me", "mentre", "més", "meu", "meus", "meva", "meves", "molt", "molta", "moltes", "molts", "mon", "mons", "n'he", "n'hi", "ne", "ni", "no", "nogensmenys", "només", "nosaltres", "nostra", "nostre", "nostres", "o", "oh", "oi", "on",...
Json - Registered: Mon Apr 22 08:04:10 GMT 2024 - Last Modified: Sat Feb 27 09:26:16 GMT 2021 - 117.3K bytes - Viewed (0) -
tensorflow/c/eager/c_api_unified_experimental_test.cc
/* Want to test simple MatMul example: [[0,0], * [[0,0], = [[0,0], [0,0]] [0,0]] [0,0]] */ // Build an abstract input tensor. int64_t dims[] = {2, 2}; // Matrices will be 2 x 2 int num_dims = sizeof(dims) / sizeof(dims[0]); float vals[] = {0.0f, 0.0f, 0.0f, 0.0f}; TFE_Context* eager_ctx = TF_ExecutionContextGetTFEContext(ctx, status.get()); TFE_TensorHandle* t =
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Fri May 19 21:44:52 GMT 2023 - 39.1K bytes - Viewed (0) -
architecture/networking/controllers.md
A queue is used to give a few properties: * Ability to serially process updates received from a variety of different sources. This avoids need for other synchronization mechanisms like mutexes. * Correctness at startup; with the sequencing above, items are only processed once all informers are synced. This means queries will not return stale data at startup. * Deduping of identical events
Plain Text - Registered: Wed Apr 24 22:53:08 GMT 2024 - Last Modified: Fri Feb 09 17:41:25 GMT 2024 - 4.9K bytes - Viewed (0) -
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);
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 23.5K bytes - Viewed (0) -
docs/es/docs/async.md
Plain Text - Registered: Sun Apr 28 07:19:10 GMT 2024 - Last Modified: Thu Apr 18 19:53:19 GMT 2024 - 24.9K bytes - Viewed (0) -
docs/pt/docs/async.md
* **Machine Learning**: Normalmente exige muita multiplicação de matrizes e vetores. Pense numa grande folha de papel com números e multiplicando todos eles juntos e ao mesmo tempo.
Plain Text - Registered: Sun Apr 28 07:19:10 GMT 2024 - Last Modified: Thu Apr 18 19:53:19 GMT 2024 - 22.2K bytes - Viewed (0) -
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.
Plain Text - Registered: Sun Apr 28 07:19:10 GMT 2024 - Last Modified: Sun Mar 31 23:52:53 GMT 2024 - 24K bytes - Viewed (0) -
RELEASE.md
matrices or batches of matrices (CPU only). * Added gradients for eigenvalues and eigenvectors computed using `self_adjoint_eig` or `self_adjoint_eigvals`. * Eliminated `batch_*` methods for most linear algebra and FFT ops and promoted the non-batch version of the ops to handle batches of matrices.
Plain Text - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Wed Apr 03 20:27:38 GMT 2024 - 727.4K bytes - Viewed (8)