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  | same oh | |
| big oh | |
| hat oh | |
| worm oh | |
| mood oh | |
| oh same | |
| big same | |
| hat same | |
| worm same | |
| mood same | 
  
    
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  | /** MathBox type declarations (autogenerated) */ | |
| /** Matrix width */ | |
| declare interface MBArea { | |
| /** Use (fast) integer lookups */ | |
| aligned?: boolean; | |
| /** Axis pair */ | |
| axes?: number[]; | |
| /** Matrix buffer height */ | |
| bufferHeight?: number; | 
  
    
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  | Range: UNKNOWN | |
| _Array: UNKNOWN | |
| _ArrayGetItem: UNKNOWN | |
| _ArraySize: UNKNOWN | |
| _AttrsListFieldInfo: UNKNOWN | |
| _BijectiveLayout: tvm::BijectiveLayout(tvm::Layout, tvm::Layout, ) | |
| _BijectiveLayout: tvm::BijectiveLayout(tvm::Layout, tvm::Layout, ) | |
| _BijectiveLayoutBackwardIndex: tvm::Array<HalideIR::Expr, void>(tvm::BijectiveLayout, tvm::Array<HalideIR::Expr, void>, ) | |
| _BijectiveLayoutBackwardIndex: tvm::Array<HalideIR::Expr, void>(tvm::BijectiveLayout, tvm::Array<HalideIR::Expr, void>, ) | |
| _BijectiveLayoutBackwardShape: tvm::Array<HalideIR::Expr, void>(tvm::BijectiveLayout, tvm::Array<HalideIR::Expr, void>, ) | 
  
    
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  | from typing import Any, Union | |
| import hashlib | |
| import pandas | |
| import numpy as np | |
| import json | |
| import os | |
| from pathlib import Path | |
| def _load_json(path: Path): | |
| return json.load(path.open('r')) | 
  
    
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  | import Glibc | |
| setenv("SWIFT_TENSORFLOW_ENABLE_DEBUG_LOGGING", "true", 1) | |
| let s = "grpc://\(String(cString: getenv("COLAB_TPU_ADDR")!))" | |
| setenv("SWIFT_TENSORFLOW_SERVER_ADDRESS", s, 1) | |
| print("SWIFT_TENSORFLOW_SERVER_ADDRESS:", String(cString: getenv("SWIFT_TENSORFLOW_SERVER_ADDRESS")!)) | |
| import TensorFlow | |
| func runTestComputation() -> Tensor<Float> { | |
| // Create two 1000x1000 tensors sampled from a random normal distribution. | 
  
    
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  | using Plots, ForwardDiff, StaticArrays, Distributions, Test | |
| g(x) = sin.(x) | |
| function newton(g, x0, n=10) | |
| out = zeros(length(x0), n) | |
| x = x0 | |
| for i in 1:n | |
| out[:, i] = x | |
| dg = ForwardDiff.jacobian(g, x) | 
  
    
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  | use std::collections::HashMap; | |
| fn main() { | |
| println!("Counting bitotal relations R: 1..n |<>| 1..m"); | |
| println!("i.e. id <= R ; R^T and id <= R^T ; R"); | |
| println!("(see: https://en.wikipedia.org/wiki/Relation_algebra, book: Algebra of Programming by Bird and Moore)"); | |
| println!(); | |
| println!("Equivalently, counting bipartite graphs between node sets of size n and m,"); | |
| println!("where every vertex has degree at least 1."); | |
| println!(); | 
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