rights reserved. Presenter: Haichen Shen, Yao Wang Amazon SageMaker Neo, Deep Engine Science Dynamic Model in TVM AWS AI© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Models with models© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Support dynamic model in TVM ● Support Any-dim in typing ● Use shape function to compute the type at runtime ● Virtual input_name = "data" input_shape = [tvm.relay.Any(), 3, 224, 224] dtype = "float32" block = get_model('resnet50_v1', pretrained=True) mod, params = relay.frontend.from_mxnet(block, shape={input_name:

instance (even indirectly) before the fork. Second, it is difficult to do zero-downtime updates in this model. Finally, since all the processes share the same port it is more difficult to monitor them individually WebSocketHandler.get_compression_options() → Dict[str, Any] | None Override to return compression options for the connection. If this method returns None (the default), compression will be disabled. If used to control the following compression options: compression_level specifies the compression level. mem_level specifies the amount of memory used for the internal compression state. These parameters are

instance (even indirectly) before the fork. Second, it is difficult to do zero-downtime updates in this model. Finally, since all the processes share the same port it is more difficult to monitor them individually WebSocketHandler.close() Configuration WebSocketHandler.check_origin() WebSocketHandler.get_compression_options() WebSocketHandler.set_nodelay()Other WebSocketHandler.ping() WebSocketHandler.on_pong() return parsed_origin.netloc.endswith(".mydomain.com") Added in version 4.0. WebSocketHandler.get_compression_options() → Dict [https://docs.python.org/3/library/typing.html#typing.Dict][str [https://docs

combinations of argument types, and applied by dis- patching to the most specific matching definition. This model is a good fit for mathematical programming, where it is unnatural for the first argument to "own" level using the @atomic, @atomicswap, and @atomicreplace macros. Specific details of the memory model and other details of the design are written in the Julia Atomics Mani- festo, which will later be it possible to run up to N Tasks on M Process, aka M:N Threading. Then a lock acquiring\releasing model for nextidx will be needed, as it is not safe to let multiple processes read-write a resource at

combinations of argument types, and applied by dis- patching to the most specific matching definition. This model is a good fit for mathematical programming, where it is unnatural for the first argument to "own" level using the @atomic, @atomicswap, and @atomicreplace macros. Specific details of the memory model and other details of the design are written in the Julia Atomics Mani- festo, which will later be it possible to run up to N Tasks on M Process, aka M:N Threading. Then a lock acquiring\releasing model for nextidx will be needed, as it is not safe to let multiple processes read-write a resource at

combinations of argument types, and applied by dis- patching to the most specific matching definition. This model is a good fit for mathematical programming, where it is unnatural for the first argument to "own" @atomicreplace macros, and @atomiconce macros.CHAPTER 25. MULTI-THREADING 326 Specific details of the memory model and other details of the design are written in the Julia Atomics Mani- festo, which will later be it possible to run up to N Tasks on M Process, aka M:N Threading. Then a lock acquiring\releasing model for nextidx will be needed, as it is not safe to let multiple processes read-write a resource at

combinations of argument types, and applied by dis- patching to the most specific matching definition. This model is a good fit for mathematical programming, where it is unnatural for the first argument to "own" @atomicreplace macros, and @atomiconce macros.CHAPTER 25. MULTI-THREADING 326 Specific details of the memory model and other details of the design are written in the Julia Atomics Mani- festo, which will later be it possible to run up to N Tasks on M Process, aka M:N Threading. Then a lock acquiring\releasing model for nextidx will be needed, as it is not safe to let multiple processes read-write a resource at

combinations of argument types, and applied by dis- patching to the most specific matching definition. This model is a good fit for mathematical programming, where it is unnatural for the first argument to "own" @atomicreplace macros, and @atomiconce macros.CHAPTER 25. MULTI-THREADING 326 Specific details of the memory model and other details of the design are written in the Julia Atomics Mani- festo, which will later be it possible to run up to N Tasks on M Process, aka M:N Threading. Then a lock acquiring\releasing model for nextidx will be needed, as it is not safe to let multiple processes read-write a resource at

combinations of argument types, and applied by dis- patching to the most specific matching definition. This model is a good fit for mathematical programming, where it is unnatural for the first argument to "own" @atomic, @atomicswap, @atomicreplace macros, and @atomiconce macros. Specific details of the memory model and other details of the design are written in the Julia Atomics Mani- festo, which will later be it possible to run up to N Tasks on M Process, aka M:N Threading. Then a lock acquiring\releasing model for nextidx will be needed, as it is not safe to let multiple processes read-write a resource at the

combinations of argument types, and applied by dis- patching to the most specific matching definition. This model is a good fit for mathematical programming, where it is unnatural for the first argument to "own" @atomic, @atomicswap, @atomicreplace macros, and @atomiconce macros. Specific details of the memory model and other details of the design are written in the Julia Atomics Mani- festo, which will later be it possible to run up to N Tasks on M Process, aka M:N Threading. Then a lock acquiring\releasing model for nextidx will be needed, as it is not safe to let multiple processes read-write a resource at the