Tornado 6.5 Documentation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 6.2 Web framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Python Module Index 257 Index 259 iiiTornado Documentation, Release 6.5.1 Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed. By using non-blocking network available in PDF and Epub formats. 6.1 User’s guide 6.1.1 Introduction Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed. By using non-blocking network0 码力 | 272 页 | 1.12 MB | 3 月前3
Tornado 6.5 DocumentationTornado [https://www.tornadoweb.org] is a Python web framework and asynchronous networking library, originally developed at FriendFeed [https://en.wikipedia.org/wiki/FriendFeed]. By using non-blocking Tornado web application Templates and UI Authentication and security Running and deploying Web framework tornado.web — RequestHandler and Application classes tornado.template — Flexible output generation httpserver — Non-blocking HTTP server tornado.httpclient — Asynchronous HTTP client tornado.httputil — Manipulate HTTP headers and URLs tornado.http1connection – HTTP/1.x client/server implementation Asynchronous0 码力 | 437 页 | 405.14 KB | 3 月前3
TVM Meetup: Quantizationdialect© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. TVM Overview Framework Graph Mxnet TF …. parsers Relay Graph Target-independent Relay passes Target-optimized graph .. More targets AutoTVM – Tuning the kernels Optimized Binary Codegen – LLVM, Cuda, C, … Framework Parsers Graph level optimizations Tensor-level optimizations Machine code generation© 2019, Amazon reserved. Quantization Appraoches in TVM Framework FP32 Graph MXNet Parser TF parser …. Relay FP32 Graph Relay Automatic Quantization Relay Int8 Graph Framework Pre-quantized Graph MXNet Parser TF Parser0 码力 | 19 页 | 489.50 KB | 5 月前3
julia 1.10.10participate as an argument in broadcasting, and by default the result is stored in an Array. This basic framework is extensible in three major ways: • Ensuring that all arguments support broadcast • Selecting SparseMatStyle, and anything of higher dimensionality falls back to the dense arbitrary-dimensional framework. These rules allow broadcasting to keep the sparse representation for operations that result in the ability to pass contextual information into show methods. The IOContext object provides this framework for associating arbitrary metadata with an IO object. For exam- ple, :compact => true adds a hinting0 码力 | 1692 页 | 6.34 MB | 3 月前3
Julia 1.10.9participate as an argument in broadcasting, and by default the result is stored in an Array. This basic framework is extensible in three major ways: • Ensuring that all arguments support broadcast • Selecting SparseMatStyle, and anything of higher dimensionality falls back to the dense arbitrary-dimensional framework. These rules allow broadcasting to keep the sparse representation for operations that result in the ability to pass contextual information into show methods. The IOContext object provides this framework for associating arbitrary metadata with an IO object. For exam- ple, :compact => true adds a hinting0 码力 | 1692 页 | 6.34 MB | 3 月前3
Julia 1.11.4participate as an argument in broadcasting, and by default the result is stored in an Array. This basic framework is extensible in three major ways: • Ensuring that all arguments support broadcast • Selecting INTERFACES 212 anything of higher dimensionality falls back to the dense arbitrary-dimensional framework. These rules allow broadcasting to keep the sparse representation for operations that result in the ability to pass contextual information into show methods. The IOContext object provides this framework for associating arbitrary metadata with an IO object. For exam- ple, :compact => true adds a hinting0 码力 | 2007 页 | 6.73 MB | 3 月前3
Julia 1.11.5 Documentationparticipate as an argument in broadcasting, and by default the result is stored in an Array. This basic framework is extensible in three major ways: • Ensuring that all arguments support broadcast • Selecting INTERFACES 212 anything of higher dimensionality falls back to the dense arbitrary-dimensional framework. These rules allow broadcasting to keep the sparse representation for operations that result in the ability to pass contextual information into show methods. The IOContext object provides this framework for associating arbitrary metadata with an IO object. For exam- ple, :compact => true adds a hinting0 码力 | 2007 页 | 6.73 MB | 3 月前3
Julia 1.11.6 Release Notesparticipate as an argument in broadcasting, and by default the result is stored in an Array. This basic framework is extensible in three major ways: • Ensuring that all arguments support broadcast • Selecting INTERFACES 212 anything of higher dimensionality falls back to the dense arbitrary-dimensional framework. These rules allow broadcasting to keep the sparse representation for operations that result in the ability to pass contextual information into show methods. The IOContext object provides this framework for associating arbitrary metadata with an IO object. For exam- ple, :compact => true adds a hinting0 码力 | 2007 页 | 6.73 MB | 3 月前3
julia 1.13.0 DEVparticipate as an argument in broadcasting, and by default the result is stored in an Array. This basic framework is extensible in three major ways: • Ensuring that all arguments support broadcast • Selecting INTERFACES 212 anything of higher dimensionality falls back to the dense arbitrary-dimensional framework. These rules allow broadcasting to keep the sparse representation for operations that result in the ability to pass contextual information into show methods. The IOContext object provides this framework for associating arbitrary metadata with an IO object. For exam- ple, :compact => true adds a hinting0 码力 | 2058 页 | 7.45 MB | 3 月前3
Julia 1.12.0 RC1participate as an argument in broadcasting, and by default the result is stored in an Array. This basic framework is extensible in three major ways: • Ensuring that all arguments support broadcast • Selecting INTERFACES 212 anything of higher dimensionality falls back to the dense arbitrary-dimensional framework. These rules allow broadcasting to keep the sparse representation for operations that result in the ability to pass contextual information into show methods. The IOContext object provides this framework for associating arbitrary metadata with an IO object. For exam- ple, :compact => true adds a hinting0 码力 | 2057 页 | 7.44 MB | 3 月前3
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