haifengkao

def remove_duplicates_ignore_timestamp(filename):
    seen = set()
    temp_filename = filename + '.temp'

    with open(filename, 'r') as f, open(temp_filename, 'w') as temp_file:
        for line in f:
            # Strip the timestamp
            stripped_line = line[12:]

            if stripped_line not in seen:

haifengkao

import os
import subprocess
import sys

# Directory paths
plugins_dir = "./plugins/"
dialogue_dir = "yamls/dialogue/"
script_dir = "yamls/script/"

# Ensure the output directories exist

haifengkao

@propertyWrapper
struct SmallNumber {
    private var maximum: Int
    private var number: Int

    var wrappedValue: Int {
        get { return number }

haifengkao

public class TaggedWeak<T: AnyObject, Hash: Hashable>: Hashable {
    public static func == (lhs: TaggedWeak<T, Hash>, rhs: TaggedWeak<T, Hash>) -> Bool {
        lhs.hash == rhs.hash
    }

    public func hash(into hasher: inout Hasher) {
        hasher.combine(hash)
    }

    public weak var value: T?

haifengkao

public struct TaggedWeak<T: AnyObject, Hash: Hashable>: Hashable {
    public static func == (lhs: TaggedWeak<T, Hash>, rhs: TaggedWeak<T, Hash>) -> Bool {
        lhs.hash == rhs.hash
    }

    public func hash(into hasher: inout Hasher) {
        hasher.combine(hash)
    }

    public weak var value: T?

haifengkao

import tensorflow as tf
import random

def genSequence():
    len = 101
    X = []
    for i in range(1, len):
        X.append([[random.random()]]*i)
    y = []
    for i in range(1, len):

haifengkao

import tensorflow as tf
import random


def genSequence():
    len = 101
    X = []
    for i in range(1, len):
        X.append([[random.random()]]*i)
    y = []

haifengkao

import Foundation

infix operator <<<: CompositionPrecedence
precedencegroup CompositionPrecedence {
    associativity: left
}

public func <<<<A, B, C>(
    _ g: @escaping (B) -> C,
    _ f: @escaping (A) -> B

haifengkao

import Cocoa


import Combine

var subscriptions = Set<AnyCancellable>()
func futureIncrement(
    integer: Int,
    afterDelay delay: TimeInterval) -> AnyPublisher<Int, Never> {
    Deferred {

haifengkao

InvalidArgumentError: 9 root error(s) found.
  (0) Invalid argument: {{function_node __inference_train_function_80125}} Compilation failure: Detected unsupported operations when trying to compile graph broadcast_weights_1_assert_broadcastable_is_valid_shape_has_valid_nonscalar_shape_true_79965_const_0[] on XLA_TPU_JIT: DenseToDenseSetOperation (No registered 'DenseToDenseSetOperation' OpKernel for XLA_TPU_JIT devices compatible with node {{node broadcast_weights_1/assert_broadcastable/is_valid_shape/has_valid_nonscalar_shape/has_invalid_dims/DenseToDenseSetOperation}}){{node broadcast_weights_1/assert_broadcastable/is_valid_shape/has_valid_nonscalar_shape/has_invalid_dims/DenseToDenseSetOperation}}
	 [[broadcast_weights_1/assert_broadcastable/is_valid_shape/has_valid_nonscalar_shape]]
	 [[broadcast_weights_1/assert_broadcastable/is_valid_shape]]
	TPU compilation failed
	 [[tpu_compile_succeeded_assert/_16364550150888184836/_30]]
	 [[TPUReplicate/_compile/_2384856891229734177/_29/_1132]]
  (1) Invalid argument