NPUOutputTensorHook构造函数【免费下载链接】tensorflowAscend TensorFlow Adapter项目地址: https://gitcode.com/cann/tensorflow功能说明NPUOutputTensorHook类的构造函数NPUOutputTensorHook作用于NPUEstimator的train、evaluate、predict流程中的Hook用于每N步或者结束时调用用户自定义的output_fn打印输出tensors。NPUOutputTensorHook类继承了LoggingTensorHook类可以调用基类的原生接口。函数原型class NPUOutputTensorHook(basic_session_run_hooks.LoggingTensorHook): def __init__(self, tensors, dependenciesNone, output_fnNone, output_every_n_steps0 )参数说明参数名输入/输出描述tensors输入输入tensor的名称集合。字典或列表格式。dependencies输入tensors对应的依赖。output_fn输入tensors的输出打印函数。output_every_n_steps输入会话执行N次和训练脚本执行结束时调用用户定义的output_fn。返回值返回NPUOutputTensorHook类对象。约束说明Iterations_per_loop1的场景下无法按照output_every_n_steps指定的值调用output_fn。调用示例from npu_bridge.npu_init import * # 定义output_fn def output_fn(inputs): device_id os.environ[ASCEND_DEVICE_ID] output_file os.path.join(/code, device_id, test_npu_output_tensor.txt) for item in inputs: content step:{},loss:{}.format(str(item[global_step]), str(item[loss])) with open(output_file, a) as f: f.write(content) f.write(\n) # 定义output_hook用于调用用户定义的output_fn tensors {global_step: global_step, loss: loss} output_hook NPUOutputTensorHook( tensors, dependenciestrain_op_list, output_fnoutput_fn, output_every_n_steps10) train_hook.append(output_hook) # 在EstimatorSpec传入hook return tf.estimator.EstimatorSpec( modemode, predictionspredictions, lossloss, train_optrain_op, training_chief_hookstrain_hook, eval_metric_opsmetrics)【免费下载链接】tensorflowAscend TensorFlow Adapter项目地址: https://gitcode.com/cann/tensorflow创作声明：本文部分内容由AI辅助生成（AIGC），仅供参考
CANN/tensorflow NPUOutputTensorHook构造函数
发布时间：2026/7/9 18:12:41
NPUOutputTensorHook构造函数【免费下载链接】tensorflowAscend TensorFlow Adapter项目地址: https://gitcode.com/cann/tensorflow功能说明NPUOutputTensorHook类的构造函数NPUOutputTensorHook作用于NPUEstimator的train、evaluate、predict流程中的Hook用于每N步或者结束时调用用户自定义的output_fn打印输出tensors。NPUOutputTensorHook类继承了LoggingTensorHook类可以调用基类的原生接口。函数原型class NPUOutputTensorHook(basic_session_run_hooks.LoggingTensorHook): def __init__(self, tensors, dependenciesNone, output_fnNone, output_every_n_steps0 )参数说明参数名输入/输出描述tensors输入输入tensor的名称集合。字典或列表格式。dependencies输入tensors对应的依赖。output_fn输入tensors的输出打印函数。output_every_n_steps输入会话执行N次和训练脚本执行结束时调用用户定义的output_fn。返回值返回NPUOutputTensorHook类对象。约束说明Iterations_per_loop1的场景下无法按照output_every_n_steps指定的值调用output_fn。调用示例from npu_bridge.npu_init import * # 定义output_fn def output_fn(inputs): device_id os.environ[ASCEND_DEVICE_ID] output_file os.path.join(/code, device_id, test_npu_output_tensor.txt) for item in inputs: content step:{},loss:{}.format(str(item[global_step]), str(item[loss])) with open(output_file, a) as f: f.write(content) f.write(\n) # 定义output_hook用于调用用户定义的output_fn tensors {global_step: global_step, loss: loss} output_hook NPUOutputTensorHook( tensors, dependenciestrain_op_list, output_fnoutput_fn, output_every_n_steps10) train_hook.append(output_hook) # 在EstimatorSpec传入hook return tf.estimator.EstimatorSpec( modemode, predictionspredictions, lossloss, train_optrain_op, training_chief_hookstrain_hook, eval_metric_opsmetrics)【免费下载链接】tensorflowAscend TensorFlow Adapter项目地址: https://gitcode.com/cann/tensorflow创作声明：本文部分内容由AI辅助生成（AIGC），仅供参考
