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.bazelrc
build:mkl --define=build_with_mkl=true --define=enable_mkl=true build:mkl --define=tensorflow_mkldnn_contraction_kernel=0 build:mkl --define=build_with_openmp=true build:mkl -c opt # config to build OneDNN backend with a user specified threadpool. build:mkl_threadpool --define=build_with_mkl=true --define=enable_mkl=true build:mkl_threadpool --define=tensorflow_mkldnn_contraction_kernel=0
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docs/en/docs/reference/request.md
You can import it directly from `fastapi`: ```python from fastapi import Request ``` !!! tip When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`.
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docs/en/docs/advanced/events.md
# Lifespan Events You can define logic (code) that should be executed before the application **starts up**. This means that this code will be executed **once**, **before** the application **starts receiving requests**. The same way, you can define logic (code) that should be executed when the application is **shutting down**. In this case, this code will be executed **once**, **after** having handled possibly **many requests**.
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fastapi/encoders.py
Python - Registered: Sun Apr 21 07:19:11 GMT 2024 - Last Modified: Thu Apr 18 21:56:59 GMT 2024 - 10.8K bytes - Viewed (0) -
docs/en/docs/reference/httpconnection.md
# `HTTPConnection` class When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`. You can import it from `fastapi.requests`: ```python from fastapi.requests import HTTPConnection ```
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fastapi/security/api_key.py
""" API key authentication using a query parameter. This defines the name of the query parameter that should be provided in the request with the API key and integrates that into the OpenAPI documentation. It extracts the key value sent in the query parameter automatically and provides it as the dependency result. But it doesn't define how to send that API key to the client. ## Usage
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docs/en/docs/reference/websockets.md
It is provided directly by Starlette, but you can import it from `fastapi`: ```python from fastapi import WebSocket ``` !!! tip When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`. ::: fastapi.WebSocket options: members: - scope - app
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tensorflow/BUILD
config_setting( name = "dynamic_loaded_kernels", define_values = { "dynamic_loaded_kernels": "true", "framework_shared_object": "true", }, visibility = ["//visibility:public"], ) config_setting( name = "using_rocm_hipcc", define_values = {"using_rocm_hipcc": "true"}, ) config_setting( name = "override_eigen_strong_inline", define_values = {"override_eigen_strong_inline": "true"},
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.cm/complex_changes.cm
# this PR, this automations will have its `if` checked to run. In a way, the `on` conditions # function as an implicit first `if` for every automation in the file. # You can define multiple automations in a .cm file, but each automation name should be unique # within the file. We keep each automation (or very closely related group of automations) in # its own file. on: - pr_created - commit
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.cm/add_usual_expert.cm
# this PR, this automations will have its `if` checked to run. In a way, the `on` conditions # function as an implicit first `if` for every automation in the file. # You can define multiple automations in a .cm file, but each automation name should be unique # within the file. We keep each automation (or very closely related group of automations) in # its own file. on: - pr_created - commit
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