ValueError: x and y must be the same size

[HeavenComet]

im new to asking for help on GitHub so here is ALL the code:

import torch
from torch import nn
import matplotlib.pyplot as plt
wieght = 0.7
bias = 0.3
start = 0
end = 1
step = 0.02
X = torch.arange(start, end, step).unsqueeze(dim=1)
y = wieght * X + bias
train_split = int(0.8 * len(X))
X_train, y_train = X[:train_split], y[:train_split]
X_test, y_test = X[train_split:], y[train_split:]
def plot_prediction(train_data = X_train,
                    train_labels = y_train,
                    test_data = X_test,
                    test_labels = y_test,
                    predictions = None):
  plt.figure(figsize=(10, 7))

  plt.scatter(train_data, train_labels, c="b", s=4, label="Training Data!")

  plt.scatter(test_data, test_labels, c="g", s=4, label="Testing Data")

  if predictions is not None:
    plt.scatter(test_data, predictions, c="r", s=4, label="Epic Gamer Predictions!!!")

  plt.legend(prop={"size":14});
class LinearRegressionModel(nn.Module):
  def __init__(self):
    super().__init__()
    self.wieght = nn.Parameter(torch.randn(1,
                                           requires_grad=True,
                                           dtype=torch.float))
    self.bias = nn.Parameter(torch.randn(1,
                                         requires_grad=True,
                                         dtype=torch.float))
  def forward(self, x: torch.Tensor) -> torch.Tensor:
    return self.wieght * X + self.bias
torch.manual_seed(42)

model0 = LinearRegressionModel()
with torch.inference_mode():
  y_preds = model0(X_test)
plot_prediction(predictions=y_preds)

error code:

ValueError                                Traceback (most recent call last)
[<ipython-input-18-7a4e64a61ee9>](https://localhost:8080/#) in <cell line: 1>()
----> 1 plot_prediction(predictions=y_preds)

3 frames
[/usr/local/lib/python3.10/dist-packages/matplotlib/axes/_axes.py](https://localhost:8080/#) in scatter(self, x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, edgecolors, plotnonfinite, **kwargs)
   4582         y = np.ma.ravel(y)
   4583         if x.size != y.size:
-> 4584             raise ValueError("x and y must be the same size")
   4585 
   4586         if s is None:

ValueError: x and y must be the same size

sorry if i gave to much code, ive spent awhile trying to figure out what this means and how to fix it and cannot for the life of me figure it out. thank you in advance!

[Perian-Yan]

Hi,
I run your code but get different errors. Note that there are double underscores on both sides of the init method. In the forward method, the argument is x, but you use X below. And, there's a typo: it's weight instead of wieght, though the result will not be affected.

Hope this helps :)

import torch
from torch import nn
import matplotlib.pyplot as plt
wieght = 0.7
bias = 0.3
start = 0
end = 1
step = 0.02
X = torch.arange(start, end, step).unsqueeze(dim=1)
y = wieght * X + bias
train_split = int(0.8 * len(X))
X_train, y_train = X[:train_split], y[:train_split]
X_test, y_test = X[train_split:], y[train_split:]

def plot_prediction(train_data = X_train,
                  train_labels = y_train,
                    test_data = X_test,
                    test_labels = y_test,
                      predictions = None):
  plt.figure(figsize=(10, 7))

  plt.scatter(train_data, train_labels, c="b", s=4, label="Training Data!")

  plt.scatter(test_data, test_labels, c="g", s=4, label="Testing Data")

  if predictions is not None:
    plt.scatter(test_data, predictions, c="r", s=4, label="Epic Gamer Predictions!!!")

  plt.legend(prop={"size":14})

class LinearRegressionModel(nn.Module):
  def __init__(self):
    super().__init__()
    self.wieght = nn.Parameter(torch.randn(1,
                          requires_grad=True,
                          dtype=torch.float))
    self.bias = nn.Parameter(torch.randn(1,
                          requires_grad=True,
                          dtype=torch.float))
  def forward(self, x: torch.Tensor) -> torch.Tensor:
    return self.wieght * x + self.bias

torch.manual_seed(42)

model0 = LinearRegressionModel()

with torch.inference_mode():
  y_preds = model0(X_test)

plot_prediction(predictions=y_preds)

[HeavenComet]

Thank you SOOOOOO much, i wouldve never figured out the error, it ran just fine!

[mrdbourke]

Thank you for helping @HeavenComet @Perian-Yan !

PS @HeavenComet , you'll notice I formatted your answer to have 3 backticks "```" around the code (this makes it easier to read).

You can also create Python formatted code with "```python""" at the start, for example:

print("Hello, world!)

The code above is rendered with:

```python
print("Hello, world!)
```

[haroon445]

The error “ValueError: x and y must be the same size” occurs in Python when the input initialized array does not have the same sizes.

To rectify this error, different solutions are used in Python, such as aligning the length of input arrays or using numpy arrays instead of lists.

I found this guide on search it was very helpful, you can check this out to resolve this error.