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ci/official/requirements_updater/numpy1_requirements/requirements_lock_3_10.txt
mdurl==0.1.2 \ --hash=sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8 \ --hash=sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba # via markdown-it-py ml-dtypes==0.4.0 \ --hash=sha256:03e7cda6ef164eed0abb31df69d2c00c3a5ab3e2610b6d4c42183a43329c72a5 \ --hash=sha256:2bb83fd064db43e67e67d021e547698af4c8d5c6190f2e9b1c53c09f6ff5531d \
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Mon Oct 28 14:33:43 UTC 2024 - 47.2K bytes - Viewed (0) -
ci/official/requirements_updater/numpy1_requirements/requirements_lock_3_12.txt
mdurl==0.1.2 \ --hash=sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8 \ --hash=sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba # via markdown-it-py ml-dtypes==0.4.0 \ --hash=sha256:03e7cda6ef164eed0abb31df69d2c00c3a5ab3e2610b6d4c42183a43329c72a5 \ --hash=sha256:2bb83fd064db43e67e67d021e547698af4c8d5c6190f2e9b1c53c09f6ff5531d \
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Mon Oct 28 14:33:43 UTC 2024 - 47.2K bytes - Viewed (0) -
requirements_lock_3_12.txt
mdurl==0.1.2 \ --hash=sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8 \ --hash=sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba # via markdown-it-py ml-dtypes==0.4.0 \ --hash=sha256:03e7cda6ef164eed0abb31df69d2c00c3a5ab3e2610b6d4c42183a43329c72a5 \ --hash=sha256:2bb83fd064db43e67e67d021e547698af4c8d5c6190f2e9b1c53c09f6ff5531d \
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Sat Oct 26 00:18:03 UTC 2024 - 48.6K bytes - Viewed (0) -
tensorflow/c/eager/c_api_unified_experimental_graph.cc
#include "tensorflow/core/framework/shape_inference.h" #include "tensorflow/core/framework/tensor_shape.h" #include "tensorflow/core/framework/types.pb.h" #include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h" #include "tensorflow/core/platform/errors.h" #include "tensorflow/core/platform/strcat.h" #include "tensorflow/core/platform/types.h" using tensorflow::dyn_cast; using tensorflow::string; using tensorflow::gtl::ArraySlice; namespace tensorflow {
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Sat Oct 12 05:11:17 UTC 2024 - 15.7K bytes - Viewed (0) -
docs/en/docs/tutorial/extra-data-types.md
* In requests and responses, handled the same as a `float`. * You can check all the valid Pydantic data types here: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic data types</a>. ## Example Here's an example *path operation* with parameters using some of the above types. //// tab | Python 3.10+ ```Python hl_lines="1 3 12-16"
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 4K bytes - Viewed (0) -
docs/uk/docs/tutorial/extra-data-types.md
* Стандартний Пайтонівський `Decimal`. * У запитах і відповідях це буде оброблено так само, як і `float`. * Ви можете перевірити всі дійсні типи даних Pydantic тут: <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">типи даних Pydantic</a>. ## Приклад Ось приклад *path operation* з параметрами, використовуючи деякі з вищезазначених типів. //// tab | Python 3.10+
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 5.8K bytes - Viewed (0) -
docs/zh/docs/tutorial/extra-data-types.md
* 生成的模式将指定这个 `str` 是 `binary` "格式"。 * `Decimal`: * 标准的 Python `Decimal`。 * 在请求和响应中被当做 `float` 一样处理。 * 您可以在这里检查所有有效的pydantic数据类型: <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">Pydantic data types</a>. ## 例子 下面是一个*路径操作*的示例,其中的参数使用了上面的一些类型。 //// tab | Python 3.10+ ```Python hl_lines="1 3 12-16" {!> ../../docs_src/extra_data_types/tutorial001_an_py310.py!} ```
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 3.9K bytes - Viewed (0) -
ci/official/requirements_updater/numpy1_requirements/requirements_lock_3_9.txt
mdurl==0.1.2 \ --hash=sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8 \ --hash=sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba # via markdown-it-py ml-dtypes==0.4.0 \ --hash=sha256:03e7cda6ef164eed0abb31df69d2c00c3a5ab3e2610b6d4c42183a43329c72a5 \ --hash=sha256:2bb83fd064db43e67e67d021e547698af4c8d5c6190f2e9b1c53c09f6ff5531d \
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Mon Oct 28 14:33:43 UTC 2024 - 47.6K bytes - Viewed (0) -
schema/schema.go
callbackTypeAfterFind callbackType = "AfterFind" ) // ErrUnsupportedDataType unsupported data type var ErrUnsupportedDataType = errors.New("unsupported data type") type Schema struct { Name string ModelType reflect.Type Table string PrioritizedPrimaryField *Field DBNames []string PrimaryFields []*Field
Registered: Sun Nov 03 09:35:10 UTC 2024 - Last Modified: Thu Jun 20 12:19:31 UTC 2024 - 13.7K bytes - Viewed (0) -
cmd/sts-handlers.go
stsRouter.Methods(http.MethodPost).MatcherFunc(func(r *http.Request, rm *mux.RouteMatch) bool { ctypeOk := wildcard.MatchSimple("application/x-www-form-urlencoded*", r.Header.Get(xhttp.ContentType)) authOk := wildcard.MatchSimple(signV4Algorithm+"*", r.Header.Get(xhttp.Authorization)) noQueries := len(r.URL.RawQuery) == 0 return ctypeOk && authOk && noQueries }).HandlerFunc(httpTraceAll(sts.AssumeRole))
Registered: Sun Nov 03 19:28:11 UTC 2024 - Last Modified: Thu Aug 15 01:29:20 UTC 2024 - 33.9K bytes - Viewed (0)