number int64 1 37 | content stringclasses 19 values | comments sequence |
|---|---|---|
37 | neural network title is fixed : Adding a title to a NeuralNetwork and moving or scaling it after does not work. The title stays and does not move respectively. | [
"I was able to shift the neural network and it moved the title as well. Can I see your code for that? I believe I fixed the issue with the title scaling. Let me know if it works for you on the latest pip update. ",
"```class BasicScene(ThreeDScene):\r\n def construct(self):\r\n # Make the neural network... |
35 | Increasing the size of the rendered NN : How do I increase the size of the rendered output? `.scale()` doesn't seem to work.
Thanks | [
"I think I may have fixed this. I am not sure which neural network you are specifically trying to render. Let me know if you can update your pip package with ```pip install --upgrade manim-ml```. Let me know if it works, and if not can you upload a picture of the failure case and code?",
"I was using MLP for a ve... |
34 | Bug fix for max_pooling_2d : Removed `remover` argument from `ReplacementTrasform` which resulted in "Could not find old_mobject in Scene" error when cleaning up the scene. | [
"Thanks for all the help!"
] |
33 | Misplacement of connections between neurons in NeuralNetworkScene : I tried to run the example code below:
```
class NeuralNetworkScene(Scene):
def construct(self):
layers = [FeedForwardLayer(3), FeedForwardLayer(5), FeedForwardLayer(3)]
nn = NeuralNetwork(layers)
self.add(nn)
nn.move_to(ORIGIN)
# nn.scale(2)
forward_propagation_animation = nn.make_forward_pass_animation(
run_time=5, passing_flash=True
)
self.play(forward_propagation_animation)
```
And everything is fine.
But when I uncomment `nn.scale(2)`, this happened:
It appears that the connections between neurons are misplaced when scaling. | [
"Sorry I never responded to this. I am pretty busy for the next few weeks, but after that I will look into this issue. ",
"Sorry this took so long for me to get back to this. I think I have fixed this. Let me know if you can update your pip package with pip install --upgrade manim-ml. Let me know if it works. ",
... |
31 | ManimML in docker : Hello,
it is possible to install ManimML in the docker Manim community docker in the jupyter notebook?
| [
"Did you end up getting this working?",
"Inside the Jupyter notebook no, I think there's a difference between the pip file paths. Instead I use the docker from the command line without the Jupyter notebook and it works fine.",
"It may have to do with the Jupyter kernel that is running inside the Docker containe... |
30 | Dropout Last Layer - option to remove node on the last layer and seed dropouts for reproducible animations : During certain tasks, the terminating layer of the neural network does not have Dropouts applied to the last layer; however, here, I wasn't able to directly find a method to prevent it. All FeedForwards are considered the same.
*Can there be an argument like:*
```py
make_neural_network_dropout_animation(
nn, dropout_rate=0.75, do_forward_pass=True, last_layer_stable=True
)
```
Would like to explore the same with the first feed-forward layer and seeding the probability distribution
Solved the above issue by introducing the following new arguments:
```py
self.play(
make_neural_network_dropout_animation(
nn, dropout_rate=0.25, do_forward_pass=True, seed=4, first_layer_stable=True, last_layer_stable=True
)
)
``` | [] |
29 | Dropout Last Layer - Should have option to remove node removal : During certain tasks, the terminating layer of the neural network does not have Dropouts applied to the last layer; however, here, I wasn't able to directly find a method to prevent it. All FeedForwards are considered the same.
*Can there be an argument like:*
```py
make_neural_network_dropout_animation(
nn, dropout_rate=0.75, do_forward_pass=True, last_layer_stable=True
)
```
Would like to explore the same with the first feed-forward layer and seeding the probability distribution
| [
"Updated the following enhancements in a fork I created -\r\n\r\n1. **Seed:** https://github.com/AmanPriyanshu/ManimML#seed-the-dropouts\r\n2. **First Layer:** https://github.com/AmanPriyanshu/ManimML#seed-the-dropouts-with-first-layer-static\r\n3. **Last Layer:** https://github.com/AmanPriyanshu/ManimML#seed-the-d... |
28 | AttributeError: MaxPooling2DLayer object has no attribute 'padding' : The code from [the example of MaxPooling2DLayer](https://github.com/helblazer811/ManimML#max-pooling) returns AttributeError. Same for [/examples/cnn/cnn_max_pool.py](https://github.com/helblazer811/ManimML/blob/main/examples/cnn/cnn_max_pool.py)
Using `manim==0.17.2` and `manim-ml==0.0.16`.
```python
from manim import *
from manim_ml.neural_network import NeuralNetwork, Convolutional2DLayer, MaxPooling2DLayer
class BasicScene(ThreeDScene):
def construct(self):
nn = NeuralNetwork(
[
Convolutional2DLayer(1, 8),
Convolutional2DLayer(3, 6, 3),
MaxPooling2DLayer(
kernel_size=2,
),
Convolutional2DLayer(5, 2, 2),
],
layer_spacing=0.25,
)
nn.move_to(ORIGIN)
self.add(nn)
forward_pass = nn.make_forward_pass_animation()
self.wait(1)
self.play(forward_pass)`
```
Stack trace:
convolutional_2d_to_convolutional_2d.py:309 in __init__ │
│ │
│ 306 │ │ self.num_output_feature_maps = self.output_layer.num_feature_maps │
│ 307 │ │ self.cell_width = self.output_layer.cell_width │
│ 308 │ │ self.stride = self.output_layer.stride │
│ ❱ 309 │ │ self.padding = self.input_layer.padding │
│ 310 │ │ self.filter_opacity = filter_opacity │
│ 311 │ │ self.cell_width = cell_width │
│ 312 │ │ self.line_color = line_color
mobject.py:660 │
│ in __getattr__ │
│ │
│ 657 │ │ │ return types.MethodType(setter, self) │
│ 658 │ │ │
│ 659 │ │ # Unhandled attribute, therefore error │
│ ❱ 660 │ │ raise AttributeError(f"{type(self).__name__} object has no attribute '{attr} │
│ 661 │ │
│ 662 │ @property │
│ 663 │ def width(self):
AttributeError: MaxPooling2DLayer object has no attribute 'padding'
| [
"Sorry about that. It should be fixed if you run `pip install --upgrade manim_ml`.",
"Thank you for the quick response and help!"
] |
26 | correct the "First Neural Network" code :
Thank you for sharing your job! @helblazer811
The second line of the "First Neural Network"
```python
from manim_ml.neural_network import Convolutional2DLayer, FeedForwardLayer, NeuralNetwork
```
should be changed as
```python
from manim_ml.neural_network.layers import Convolutional2DLayer, FeedForwardLayer
from manim_ml.neural_network.neural_network import NeuralNetwork
```
I hope this project gets better and better.
| [
"Thanks so much for the catch! I'm glad you like the project. I think I just forgot to add the manim_ml/neural_network/__init__.py file which defined all of these import shortcuts in the most recent pypi package. It should be good now if you install again by running `pip install --upgrade manim_ml`. Let me know if ... |
23 | Allow for passing layers as a dictionary. : Allow for passing layers as a dictionary as follows:
```python
nn = NeuralNetwork({
"image_layer": ImageLayer(numpy_image, height=1.5),
"conv_1_layer": Convolutional2DLayer(1, 7, 3, filter_spacing=0.32),
"feed_forward_1_layer": FeedForwardLayer(3),
},
layer_spacing=0.25,
)
```
The main purpose of this is so that we can add operations later on that reference the layers by name like adding a residual connection `nn.add_connection("image_layer", "feed_forward_1_layer")`. | [
"This should be good now. "
] |
22 | filename change in layers : after installing manim_ml on my anaconda env, i noticed that the import in the example
```from manim_ml.neural_network.layers.convolutional_2d import Convolutional2DLayer```
didn't work. After digging into the site packages, and locating why the rest of the imports due work i found that it was because the file is called `convolutional2d.py` and not `convolutional_2d.py` making this import in the example not work. Seems the pip build has a different name for this [file](https://github.com/helblazer811/ManimML/blob/main/manim_ml/neural_network/layers/convolutional_2d.py)
I checked by reinstalling the latest build from pip on 26.01.2023. | [
"Thanks! Let me update fix this bug and then update the pip registry. ",
"I updated the pip registry. Can you let me know if it works now? Sorry if the project is a bit unstable right now. It is still under development. ",
"The image file that I reference in the example will likely have to be removed or replace... |
21 | Clean up the namespace for layers : It would be nice if I could import a bunch of layers from one namespace file instead of from each of the files individually,
this would shorten the length of the imports at the beginning of files. | [
"This should be fixed as of https://github.com/helblazer811/ManimML/commit/b767b9abeec6d3202ab034dc376f77aafea0423f"
] |
16 | 2D Max Pooling Layer : The max pooling visualization can work as follows:
1. Draw boxes around the max pooling regions in the input feature maps.
2. Randomly highlight a square from one of the boxes.
3. Make an invisible set of reduced width and height output feature maps.
4. Move each square to its corresponding location in the output feature map with an animation.
5. Make the output feature map appear.
If this is too busy then maybe an alternative is:
1. Draw boxes around the max pooling regions in the input feature maps.
2. Make an invisible set of reduced width and height output feature maps.
3. Resize and translate each square to the appropriate location in the output feature maps.
4. Make the output feature map appear. | [
"This is done as of https://github.com/helblazer811/ManimML/commit/46958ea293e9d54cd0057fb6b0cb6458c331dabe\r\n"
] |
13 | Activation Functions : I want to visualize activation functions. I can envision two different ways of doing this.
1. Show activation functions as their own layer.
2. Show activation functions above existing layers with a certain symbol.
I am in favor of showing the activation function above existing layers because it will not interfere with existing visualizations like FeedForwardToFeedForward Convolutional3dToConvolutional3D.
A possible way to allow for this would to be to add a string optional parameter to layers like FeedForward and Convolutional3d.
```python
nn = NeuralNetwork([
ImageLayer(numpy_image, height=1.5),
Convolutional3DLayer(1, 7, 7, 3, 3, filter_spacing=0.32, activation="relu"),
Convolutional3DLayer(3, 5, 5, 3, 3, filter_spacing=0.32, activation="relu"),
FeedForwardLayer(3, activation="sigmoid"),
],
layer_spacing=0.25,
)
```
Another way of doing it could be to pass a function or callable object (the callable object could also have a name) instead of a string, which would allow for custom activation functions.
```python
def step_function(input):
return 0 if input < 0 else return 1
nn = NeuralNetwork([
ImageLayer(numpy_image, height=1.5),
Convolutional3DLayer(1, 7, 7, 3, 3, filter_spacing=0.32, activation=step_function),
Convolutional3DLayer(3, 5, 5, 3, 3, filter_spacing=0.32, activation="relu"),
FeedForwardLayer(3, activation="sigmoid"),
],
layer_spacing=0.25,
)
```
A small coordinate frame with a function visualization can be shown above the layer that is being "activated" and that small function can be highlighted whenever there is a forward pass.
| [
"A potential way to define activation functions could be as follows:\r\n\r\n```python\r\n\r\nclass ActivationFunction(ABC):\r\n\r\n def __init__(self, function_name=None, x_range=[-1, 1], y_range=[-1, 1]):\r\n self.function_name = function_name\r\n self.x_range = x_range\r\n self.y_ran... |
8 | Convolutional Neural Network Filter Rendering Order : The filters in the CNN visualizations render behind the feature maps, which is not desirable. | [
"This should be fixed by using the `shape_in_3d=True` option for mobjects. "
] |
6 | Residual Connections : I would like to add support for residual connections (ResNet) to the neural network rendering system. | [
"I added basic residual connections, but now I still want to add the plus icon when adding the residual input to a layer to emphasize the operation that is happening. ",
"This should be done now. "
] |
3 | [BUG] update some of the examples : I updated most of the examples, in particular: `disentanglement` `cnn` `vae`.
`interpolation` still doesn't work, and `gan` has some positioning issues but at least it renders.
Thanks for the cool library btw! l think having working/updated examples would increase it's visibility and usefulness :)
| [
"Thanks so much! I'm glad you like the project and totally agree. I definitely need to start back-testing all of the examples when I introduce more changes."
] |
2 | PyPi out of date : When I `pip install manim_ml` it doesn't include any of the examples in the README. It also doesn't have many of the modules you'd expect. For example, `manim_ml.neural_networks` doesn't exist. As a workaround I've manually installed dependencies and added a clone of the latest commit to my python path. However, it would be nice to be able to install it via pip. | [
"Yeah. Sorry about that. I just uploaded a new version to pip. Let me know if you need anything else. The project is changing relatively quickly, so sorry if there are any bugs or unfinished pieces. ",
"Thank you! This package is an awesome addition to manim.",
"Oh hmmm, even after grabbing 0.9.0 from PyPi. I s... |
1 | Add GIFs to Readme : | [] |
37 | neural network title is fixed : Adding a title to a NeuralNetwork and moving or scaling it after does not work. The title stays and does not move respectively. | [
"I was able to shift the neural network and it moved the title as well. Can I see your code for that? I believe I fixed the issue with the title scaling. Let me know if it works for you on the latest pip update. ",
"```class BasicScene(ThreeDScene):\r\n def construct(self):\r\n # Make the neural network... |
35 | Increasing the size of the rendered NN : How do I increase the size of the rendered output? `.scale()` doesn't seem to work.
Thanks | [
"I think I may have fixed this. I am not sure which neural network you are specifically trying to render. Let me know if you can update your pip package with ```pip install --upgrade manim-ml```. Let me know if it works, and if not can you upload a picture of the failure case and code?",
"I was using MLP for a ve... |
34 | Bug fix for max_pooling_2d : Removed `remover` argument from `ReplacementTrasform` which resulted in "Could not find old_mobject in Scene" error when cleaning up the scene. | [
"Thanks for all the help!"
] |
33 | Misplacement of connections between neurons in NeuralNetworkScene : I tried to run the example code below:
```
class NeuralNetworkScene(Scene):
def construct(self):
layers = [FeedForwardLayer(3), FeedForwardLayer(5), FeedForwardLayer(3)]
nn = NeuralNetwork(layers)
self.add(nn)
nn.move_to(ORIGIN)
# nn.scale(2)
forward_propagation_animation = nn.make_forward_pass_animation(
run_time=5, passing_flash=True
)
self.play(forward_propagation_animation)
```
And everything is fine.
But when I uncomment `nn.scale(2)`, this happened:
It appears that the connections between neurons are misplaced when scaling. | [
"Sorry I never responded to this. I am pretty busy for the next few weeks, but after that I will look into this issue. ",
"Sorry this took so long for me to get back to this. I think I have fixed this. Let me know if you can update your pip package with pip install --upgrade manim-ml. Let me know if it works. ",
... |
31 | ManimML in docker : Hello,
it is possible to install ManimML in the docker Manim community docker in the jupyter notebook?
| [
"Did you end up getting this working?",
"Inside the Jupyter notebook no, I think there's a difference between the pip file paths. Instead I use the docker from the command line without the Jupyter notebook and it works fine.",
"It may have to do with the Jupyter kernel that is running inside the Docker containe... |
30 | Dropout Last Layer - option to remove node on the last layer and seed dropouts for reproducible animations : During certain tasks, the terminating layer of the neural network does not have Dropouts applied to the last layer; however, here, I wasn't able to directly find a method to prevent it. All FeedForwards are considered the same.
*Can there be an argument like:*
```py
make_neural_network_dropout_animation(
nn, dropout_rate=0.75, do_forward_pass=True, last_layer_stable=True
)
```
Would like to explore the same with the first feed-forward layer and seeding the probability distribution
Solved the above issue by introducing the following new arguments:
```py
self.play(
make_neural_network_dropout_animation(
nn, dropout_rate=0.25, do_forward_pass=True, seed=4, first_layer_stable=True, last_layer_stable=True
)
)
``` | [] |
29 | Dropout Last Layer - Should have option to remove node removal : During certain tasks, the terminating layer of the neural network does not have Dropouts applied to the last layer; however, here, I wasn't able to directly find a method to prevent it. All FeedForwards are considered the same.
*Can there be an argument like:*
```py
make_neural_network_dropout_animation(
nn, dropout_rate=0.75, do_forward_pass=True, last_layer_stable=True
)
```
Would like to explore the same with the first feed-forward layer and seeding the probability distribution
| [
"Updated the following enhancements in a fork I created -\r\n\r\n1. **Seed:** https://github.com/AmanPriyanshu/ManimML#seed-the-dropouts\r\n2. **First Layer:** https://github.com/AmanPriyanshu/ManimML#seed-the-dropouts-with-first-layer-static\r\n3. **Last Layer:** https://github.com/AmanPriyanshu/ManimML#seed-the-d... |
28 | AttributeError: MaxPooling2DLayer object has no attribute 'padding' : The code from [the example of MaxPooling2DLayer](https://github.com/helblazer811/ManimML#max-pooling) returns AttributeError. Same for [/examples/cnn/cnn_max_pool.py](https://github.com/helblazer811/ManimML/blob/main/examples/cnn/cnn_max_pool.py)
Using `manim==0.17.2` and `manim-ml==0.0.16`.
```python
from manim import *
from manim_ml.neural_network import NeuralNetwork, Convolutional2DLayer, MaxPooling2DLayer
class BasicScene(ThreeDScene):
def construct(self):
nn = NeuralNetwork(
[
Convolutional2DLayer(1, 8),
Convolutional2DLayer(3, 6, 3),
MaxPooling2DLayer(
kernel_size=2,
),
Convolutional2DLayer(5, 2, 2),
],
layer_spacing=0.25,
)
nn.move_to(ORIGIN)
self.add(nn)
forward_pass = nn.make_forward_pass_animation()
self.wait(1)
self.play(forward_pass)`
```
Stack trace:
convolutional_2d_to_convolutional_2d.py:309 in __init__ │
│ │
│ 306 │ │ self.num_output_feature_maps = self.output_layer.num_feature_maps │
│ 307 │ │ self.cell_width = self.output_layer.cell_width │
│ 308 │ │ self.stride = self.output_layer.stride │
│ ❱ 309 │ │ self.padding = self.input_layer.padding │
│ 310 │ │ self.filter_opacity = filter_opacity │
│ 311 │ │ self.cell_width = cell_width │
│ 312 │ │ self.line_color = line_color
mobject.py:660 │
│ in __getattr__ │
│ │
│ 657 │ │ │ return types.MethodType(setter, self) │
│ 658 │ │ │
│ 659 │ │ # Unhandled attribute, therefore error │
│ ❱ 660 │ │ raise AttributeError(f"{type(self).__name__} object has no attribute '{attr} │
│ 661 │ │
│ 662 │ @property │
│ 663 │ def width(self):
AttributeError: MaxPooling2DLayer object has no attribute 'padding'
| [
"Sorry about that. It should be fixed if you run `pip install --upgrade manim_ml`.",
"Thank you for the quick response and help!"
] |
26 | correct the "First Neural Network" code :
Thank you for sharing your job! @helblazer811
The second line of the "First Neural Network"
```python
from manim_ml.neural_network import Convolutional2DLayer, FeedForwardLayer, NeuralNetwork
```
should be changed as
```python
from manim_ml.neural_network.layers import Convolutional2DLayer, FeedForwardLayer
from manim_ml.neural_network.neural_network import NeuralNetwork
```
I hope this project gets better and better.
| [
"Thanks so much for the catch! I'm glad you like the project. I think I just forgot to add the manim_ml/neural_network/__init__.py file which defined all of these import shortcuts in the most recent pypi package. It should be good now if you install again by running `pip install --upgrade manim_ml`. Let me know if ... |
23 | Allow for passing layers as a dictionary. : Allow for passing layers as a dictionary as follows:
```python
nn = NeuralNetwork({
"image_layer": ImageLayer(numpy_image, height=1.5),
"conv_1_layer": Convolutional2DLayer(1, 7, 3, filter_spacing=0.32),
"feed_forward_1_layer": FeedForwardLayer(3),
},
layer_spacing=0.25,
)
```
The main purpose of this is so that we can add operations later on that reference the layers by name like adding a residual connection `nn.add_connection("image_layer", "feed_forward_1_layer")`. | [
"This should be good now. "
] |
22 | filename change in layers : after installing manim_ml on my anaconda env, i noticed that the import in the example
```from manim_ml.neural_network.layers.convolutional_2d import Convolutional2DLayer```
didn't work. After digging into the site packages, and locating why the rest of the imports due work i found that it was because the file is called `convolutional2d.py` and not `convolutional_2d.py` making this import in the example not work. Seems the pip build has a different name for this [file](https://github.com/helblazer811/ManimML/blob/main/manim_ml/neural_network/layers/convolutional_2d.py)
I checked by reinstalling the latest build from pip on 26.01.2023. | [
"Thanks! Let me update fix this bug and then update the pip registry. ",
"I updated the pip registry. Can you let me know if it works now? Sorry if the project is a bit unstable right now. It is still under development. ",
"The image file that I reference in the example will likely have to be removed or replace... |
21 | Clean up the namespace for layers : It would be nice if I could import a bunch of layers from one namespace file instead of from each of the files individually,
this would shorten the length of the imports at the beginning of files. | [
"This should be fixed as of https://github.com/helblazer811/ManimML/commit/b767b9abeec6d3202ab034dc376f77aafea0423f"
] |
16 | 2D Max Pooling Layer : The max pooling visualization can work as follows:
1. Draw boxes around the max pooling regions in the input feature maps.
2. Randomly highlight a square from one of the boxes.
3. Make an invisible set of reduced width and height output feature maps.
4. Move each square to its corresponding location in the output feature map with an animation.
5. Make the output feature map appear.
If this is too busy then maybe an alternative is:
1. Draw boxes around the max pooling regions in the input feature maps.
2. Make an invisible set of reduced width and height output feature maps.
3. Resize and translate each square to the appropriate location in the output feature maps.
4. Make the output feature map appear. | [
"This is done as of https://github.com/helblazer811/ManimML/commit/46958ea293e9d54cd0057fb6b0cb6458c331dabe\r\n"
] |
13 | Activation Functions : I want to visualize activation functions. I can envision two different ways of doing this.
1. Show activation functions as their own layer.
2. Show activation functions above existing layers with a certain symbol.
I am in favor of showing the activation function above existing layers because it will not interfere with existing visualizations like FeedForwardToFeedForward Convolutional3dToConvolutional3D.
A possible way to allow for this would to be to add a string optional parameter to layers like FeedForward and Convolutional3d.
```python
nn = NeuralNetwork([
ImageLayer(numpy_image, height=1.5),
Convolutional3DLayer(1, 7, 7, 3, 3, filter_spacing=0.32, activation="relu"),
Convolutional3DLayer(3, 5, 5, 3, 3, filter_spacing=0.32, activation="relu"),
FeedForwardLayer(3, activation="sigmoid"),
],
layer_spacing=0.25,
)
```
Another way of doing it could be to pass a function or callable object (the callable object could also have a name) instead of a string, which would allow for custom activation functions.
```python
def step_function(input):
return 0 if input < 0 else return 1
nn = NeuralNetwork([
ImageLayer(numpy_image, height=1.5),
Convolutional3DLayer(1, 7, 7, 3, 3, filter_spacing=0.32, activation=step_function),
Convolutional3DLayer(3, 5, 5, 3, 3, filter_spacing=0.32, activation="relu"),
FeedForwardLayer(3, activation="sigmoid"),
],
layer_spacing=0.25,
)
```
A small coordinate frame with a function visualization can be shown above the layer that is being "activated" and that small function can be highlighted whenever there is a forward pass.
| [
"A potential way to define activation functions could be as follows:\r\n\r\n```python\r\n\r\nclass ActivationFunction(ABC):\r\n\r\n def __init__(self, function_name=None, x_range=[-1, 1], y_range=[-1, 1]):\r\n self.function_name = function_name\r\n self.x_range = x_range\r\n self.y_ran... |
8 | Convolutional Neural Network Filter Rendering Order : The filters in the CNN visualizations render behind the feature maps, which is not desirable. | [
"This should be fixed by using the `shape_in_3d=True` option for mobjects. "
] |
6 | Residual Connections : I would like to add support for residual connections (ResNet) to the neural network rendering system. | [
"I added basic residual connections, but now I still want to add the plus icon when adding the residual input to a layer to emphasize the operation that is happening. ",
"This should be done now. "
] |
3 | [BUG] update some of the examples : I updated most of the examples, in particular: `disentanglement` `cnn` `vae`.
`interpolation` still doesn't work, and `gan` has some positioning issues but at least it renders.
Thanks for the cool library btw! l think having working/updated examples would increase it's visibility and usefulness :)
| [
"Thanks so much! I'm glad you like the project and totally agree. I definitely need to start back-testing all of the examples when I introduce more changes."
] |
2 | PyPi out of date : When I `pip install manim_ml` it doesn't include any of the examples in the README. It also doesn't have many of the modules you'd expect. For example, `manim_ml.neural_networks` doesn't exist. As a workaround I've manually installed dependencies and added a clone of the latest commit to my python path. However, it would be nice to be able to install it via pip. | [
"Yeah. Sorry about that. I just uploaded a new version to pip. Let me know if you need anything else. The project is changing relatively quickly, so sorry if there are any bugs or unfinished pieces. ",
"Thank you! This package is an awesome addition to manim.",
"Oh hmmm, even after grabbing 0.9.0 from PyPi. I s... |
1 | Add GIFs to Readme : | [] |
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