The other reason can be to have the same code for both numpy array and tensor. That is not wanted by TensorFlow a Tensor and a np array are two completely different things and should have different APIs. As in my case, tf.searchsorted expects float64 even I only use float32 in my cod...
(*args, **kwargs or {}) File "/Users/alyears/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/_refs/__init__.py", line 4254, in empty_like return torch.empty_strided( TypeError: Cannot convert a MPS Tensor to float64 dtype as the MPS framework doesn't support float...
【macos】def..真实艰辛啊,一直在拍错,pt的包下了,macos的sh改完了,但又出来这个问题,网上实在无解求助贴吧TypeError: Cannot convert a MPS Tensor to float64
MakeArgument("values", tensor.float_data)]) init_net.op.extend([op]) init_net.op.extend([core.CreateOperator("ConstantFill", [], [input_name], shape=[1])]) return init_net Example 2Source File: metric_learning_test.py From tf-slim with Apache License 2.0 6 votes def convert_to...
inp = tf.convert_to_tensor( np.random.randn(batch_size, input_size), dtype=tf.float32) inputs.append(inp) initializer = tf.random_uniform_initializer(-0.01,0.01, seed=19890212)withtf.variable_scope("basic", initializer=initializer):
tf.convert_to_tensor import tensorflow as tf import numpy as np def my_func(arg): arg = tf.convert_to_tensor(arg, dtype=tf.float32) return arg # The following calls are equivalent. value_1 = my_func(tf.constant([[1.0, 2.0], [3.0, 4.0]]))...
TypeError: can't convert CUDA tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first. 解决办法: output.data.cpu().numpy() 把CUDA tensor格式的数据改成numpy时,需要先将其转换成cpu float-tensor随后再转到numpy格式。 numpy不能读取CUDA tensor 需要将它转化为 CPU tensor。
TypeError: can't convert CUDA tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first. 1. 意思是:如果想把CUDA tensor格式的数据改成numpy时,需要先将其转换成cpu float-tensor随后再转到numpy格式。 numpy...
convert_to_tensor(arg, dtype=tf.float32) return arg # The following calls are equivalent. value_1 = my_func(tf.constant([[1.0, 2.0], [3.0, 4.0]])) print(value_1) tf.Tensor( [[1. 2.] [3. 4.]], shape=(2, 2), dtype=float32) value_2 = my_func([[1.0, 2.0], [3.0, ...
x:tf.Tensor([1.2.3.4.],shape=(4,),dtype=float64) 注:本文由VeryToolz翻译自Python - tensorflow.convert_to_tensor(),非经特殊声明,文中代码和图片版权归原作者aman neekhara所有,本译文的传播和使用请遵循“署名-相同方式共享 4.0 国际 (CC BY-SA 4.0)”协议。