Added various PyTorch wrapper nodes to generate tensors.

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HowToSD
2025-02-27 13:05:17 -08:00
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| [Pt From Image](pt_from_image.md) | Casts an Image tensor as a PyTorch tensor. |
| [Pt From Latent](pt_from_latent.md) | Casts a latent tensor as a PyTorch tensor. |
| [Pt From Numpy](pt_from_numpy.md) | Converts a NumPy ndarray to a PyTorch tensor while preserving its data type. |
| [Pt Full](pt_full.md) | Creates a PyTorch tensor filled with a specified value using the size entered in the text field. |
| [Pt Int Create](pt_int_create.md) | Creates a PyTorch tensor with 32-bit integer |
| [Pt Ones](pt_ones.md) | Creates a PyTorch tensor of ones using the size entered in the text field. |
| [Pt Rand](pt_rand.md) | Creates a PyTorch tensor with values sampled from a uniform distribution |
| [Pt Rand Int](pt_rand_int.md) | Creates a PyTorch tensor filled with random integers within a specified range using the size entered in the text field. |
| [Pt Randn](pt_randn.md) | Creates a PyTorch tensor with values sampled from a standard normal distribution (mean=0, std=1) |
| [Pt Zeros](pt_zeros.md) | Creates a PyTorch tensor of zeros using the size entered in the text field. |
## PyTorch wrapper - Tensor data conversion
| Node | Description |
| --- | --- |
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| [Pt To Latent](pt_to_latent.md) | Casts a PyTorch tensor as a latent tensor. |
| [Pt To Numpy](pt_to_numpy.md) | Converts PyTorch tensor to NumPy ndarray. |
| [Pt To Rgb Tensors](pt_to_rgb_tensors.md) | Splits a PyTorch tensor into R, G, and B tensors. |
## PyTorch wrapper - Transform
| Node | Description |
| --- | --- |
| [Pt Permute](pt_permute.md) | Permutes the dimensions of a PyTorch tensor according to the specified order. |
| [Pt Squeeze](pt_squeeze.md) | Removes a dimension at the specified position in the input tensor if it is of size 1. |
| [Pt Unsqueeze](pt_unsqueeze.md) | Adds a singleton dimension at the specified position in the input tensor. |
| [Pt View](pt_view.md) | Reshapes a PyTorch tensor into a specified shape using `torch.view()`. |
## Python wrapper
| Node | Description |
| --- | --- |
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# Pt Full
Creates a PyTorch tensor filled with a specified value using the size entered in the text field.
For example, if you want to create a 4D tensor of batch size=2, channel=3, height=96, width=32 filled with 7, enter:
[2,3,96,32] for size and 7 for value.
## Input
| Name | Data type |
|---|---|
| value | String |
| size | String |
| data_type | |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Tensor creation
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
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# Pt Ones
Creates a PyTorch tensor of ones using the size entered in the text field.
For example, if you want to create a 4D tensor of batch size=2, channel=3, height=96, width=32, enter:
[2,3,96,32]
## Input
| Name | Data type |
|---|---|
| size | String |
| data_type | |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Tensor creation
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# Pt Permute
Permutes the dimensions of a PyTorch tensor according to the specified order.
For example, if a tensor has shape (2, 3, 96, 32) and `new_axes="[0, 3, 1, 2]"`,
the output will have shape (2, 32, 3, 96).
Specify the new axis order in the `new_axes` field using brackets, as shown below:
```
[0, 3, 1, 2]
```
## Input
| Name | Data type |
|---|---|
| tens | Tensor |
| new_axes | String |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Transform
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# Pt Rand
Creates a PyTorch tensor with values sampled from a uniform distribution
using the size entered in the text field.
For example, if you want to create a 4D tensor of batch size=2, channel=3, height=96, width=32, enter:
[2,3,96,32]
## Input
| Name | Data type |
|---|---|
| size | String |
| data_type | |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Tensor creation
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
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# Pt Rand Int
Creates a PyTorch tensor filled with random integers within a specified range using the size entered in the text field.
For example, if you want to create a 4D tensor of batch size=2, channel=3, height=96, width=32 with random integers in the range [0, 10),
enter [2,3,96,32] for size, 0 for min_value, and 10 for max_value.
## Input
| Name | Data type |
|---|---|
| min_value | Int |
| max_value | Int |
| size | String |
| data_type | |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Tensor creation
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
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# Pt Randn
Creates a PyTorch tensor with values sampled from a standard normal distribution (mean=0, std=1)
using the size entered in the text field.
For example, if you want to create a 4D tensor of batch size=2, channel=3, height=96, width=32, enter:
[2,3,96,32]
## Input
| Name | Data type |
|---|---|
| size | String |
| data_type | |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Tensor creation
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# Pt Squeeze
Removes a dimension at the specified position in the input tensor if it is of size 1.
Specifying a tuple of dimensions is not supported yet.
## Input
| Name | Data type |
|---|---|
| tens | Tensor |
| dim | Int |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Transform
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# Pt Unsqueeze
Adds a singleton dimension at the specified position in the input tensor.
For example, if a tensor has shape (3, 4) and `dim=1`, the output will have shape (3, 1, 4).
## Input
| Name | Data type |
|---|---|
| tens | Tensor |
| dim | Int |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Transform
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# Pt View
Reshapes a PyTorch tensor into a specified shape using `torch.view()`.
The total number of elements must remain unchanged.
For example, if a tensor has shape (2, 3, 4), and `new_shape="[6, 4]"`,
the output will have shape (6, 4).
Use -1 to automatically infer a dimension, e.g.:
```
[2, -1]
```
## Input
| Name | Data type |
|---|---|
| tens | Tensor |
| new_shape | String |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Transform
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# Pt Zeros
Creates a PyTorch tensor of zeros using the size entered in the text field.
For example, if you want to create a 4D tensor of batch size=2, channel=3, height=96, width=32, enter:
[2,3,96,32]
## Input
| Name | Data type |
|---|---|
| size | String |
| data_type | |
## Output
| Data type |
|---|
| Tensor |
<HR>
Category: PyTorch wrapper - Tensor creation
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.