codegen ● Template path: python/tvm/relay/op/contrib/ /extern_op.py ● Boolean functions in the template def conv2d(attrs, args): return is_float32(args) Relay operator name Operator Implement extern operator functions, OR 2. Implement a graph annotator© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Graph Partitioning Use external functions to wrap annotated subgraphs subgraphs extern function data weight1 weight3 weight2 output data weight1 weight3 weight2 output data weight1 weight3 weight2 output What are not supported yet? ● Duplicated inputs optimization

works like a checklist, flagging transactions based on preset criteria. In contrast, an LLM agent functions more like a seasoned investigator, evaluating context, considering subtle patterns, and identifying components: 01 Model The LLM powering the agent’s reasoning and decision-making 02 Tools External functions or APIs the agent can use to take action 03 Instructions Explicit guidelines and guardrails defining Python 1 2 3 4 5 6 7 8 8 10 11 12 from import def agents Agent, WebSearchTool, function_tool @function_tool save_results(output): db.insert({ : output, : datetime.time()}) return

model with 70B parameters 5/24: Google introduces AI overviews to augment its search functions 9/24: Alibaba releases 100 open-source Qwen 2.5 models, with performance in line with but a convergence. Horizontal platforms will push breadth, stitching together knowledge across functions; specialists will push depth, delivering AI that speaks the language of compliance, contracts reliance on costly, time-intensive experimental methods, enabling rapid exploration of protein function and design. Size of Major Protein Sequencing Models (B Parameters) – 2020-2024, per Stanford

Al.Labs 阿里巴巴人工智能实验室 PowerVR support by TVM NNVM Compiler -Execution graph -Model layers functions Computation Graph Optimizations -Param TvM Tensor Operators &

Affiliates. All rights reserved. Support dynamic model in TVM ● Support Any-dim in typing ● Use shape function to compute the type at runtime ● Virtual machine as a new runtime for Relay ● Dynamic codegen fp32>© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Gradual typing: shape function ● Relax type inference/checking for Any at compilation time broadcast: fn(Tensor<(Any, Any), fp32> Affiliates. All rights reserved. Gradual typing: shape function ● Relax type inference/checking for Any at compilation time ● Register a shape function for operator to check the type and compute the output

Single unified module/pass, type system, with function variants supportCompilation Flow under the New Infra IRModule (relay::Function) IRModule (te::Function, ExternFunc, …) runtime::Module High-level High-level optimizations (Auto) Schedules
 Low-level optimizations Codegen Import LowerMixed Function Variants in the Same Module def @relay_add_one(%x : Tensor((10,), f32)) { call_destination_passing Compilers MLIR-TF Function relay::Function TorchScript IR Translation Custom Packaging runtime::Module ExternModule DSOModule Function in Other IR ExternFunc te::Function IRModule Custom

DeepSeekMoE in this section. For other tiny details (e.g., layer normalization and the activation function in FFNs), unless specifically stated, DeepSeek-V2 follows the settings of DeepSeek 67B (DeepSeek-AI (25) where ?1 is a hyper-parameter called expert-level balance factor; 1(·) denotes the indicator function; and ? denotes the number of tokens in a sequence. Device-Level Balance Loss. In addition to the example of MATH. 45 PROMPT You are an expert Python programmer, and here is your task: Write a function to find the similar elements from the given two tuple lists. Your code should pass these tests:

CPU FPGA CPU CPU FPGA Parallel Subgraphs© Copyright 2018 Xilinx Registering external accelerator function @reg.register_compute("accel", level=15) def compute_accel(attrs,inputs,outputs): op = 'accel' in inpt.shape] for inpt in inputs] out_shapes = [[int(i) for i in outputs[0].shape]] # EXTERNAL FUNCTION TO RUN THE FUSED OPERATION out = tvm.extern(outputs[0].shape, inputs, lambda ins, outs: tvm.call_packed('tvm "num_inputs": "1", "num_outputs": "1" }, "inputs": [[1, 0, 0]] }, >> 11 Calls XDNN’s TVM registered function to access the FPGA runtime APIs© Copyright 2018 Xilinx Registering TVM op in Python at runtime

predicted token. The Gemini temperature control can be understood in a similar way to the softmax function used in machine learning. A low temperature setting mirrors a low softmax temperature (T), emphasizing print("Files renamed successfully.") ``` Output The code calls the `toUpperCase` function to convert `prefix` to uppercase, but that function is not defined. To fix this issue, you can use the `upper()` method of

cuUBLAS/VcuDNNVCUTL， Blade Kernel Lib S， ation 计算平台事业部 COMPUTING PLATFORM Weight Adjustment IHomogeneous 剂Function: f(cx) =cfGx) Conv/MatMu1l 计算平台事业部 COMPUTING PLATFORM /c Weight Adjustment