Skip to main content

One Path to Bankruptcy for Replit

User trying to import a module that's not installed. Instead of bumping him and telling her to use a different workspace on which the module *is* installed, use compute resources to try and install.. nuts.. Starting with : from transformers import TFAutoModelForSeq2SeqLM, AutoTokenizer import gradio as gr model = TFAutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small") tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-small") def gen_text(input_string, max_length):     inputs = tokenizer(input_string, return_tensors="pt")     outputs = model.generate(**inputs, max_length=max_length)     final_text = tokenizer.batch_decode(outputs[0], skip_special_tokens=True)     return (final_text) demo = gr.Interface(                                                          fn=gen_text,     ...
Post a Comment

What Do Generators Give You

Being rusty, I did

hands.extend( (b_hand + [card] for card in joker_cards('red'))) 

And, of course, I actually meant a list comprehension. I actually made myself look better here - I had first done list.append - which gave me a list of lists of lists, rather than a list of lists, which was what I wanted.. if it worked - which it didn't of course - giving me a generator expression. chatGPT told me to wrap the generator expression in list(), which I did - not thinking clearly..

All I needed was:

hands.extend( [b_hand + [card] for card in joker_cards('red')] ) 

Which leads us to the question of generator expressions - what? why? Where?..

What

A way to create generators (type of iterable you can use to create lazy sequences) without having to define a function
A Genertor function allows you to declare a function that behaves like an iterator - now you can loop around this function call

Example

(expression for item in iterable)
Note that [ ] instead of ( ) would be list comprehension
In the list-comp case, all the computation is done in one shot to build the list

Where

Use them when you want to produce a sequence of values, one at a time, on demand

Why?

Memory is saved as items are only produced as required

Labels:

Comments

Post a Comment

Popular posts from this blog

Align an Embedded Image in Jupyter Markdown

Nice thing is that you don't have to depend on the image existing as a separate file that you can refer to. You can embed it like an image in an email - you get the idea. Jupyter takes care of this for you in the .ipynb file. But, by default, the image is aligned center and is default size. What if you want to set the size? If it were an external file, then you can just resort to standard HTML. But, you want a fully self contained notebook. So? In one cell, above this one, NOT markdown, but code, have an HTML magic where you specify CSS that applies to this TAG. In the cell of interest, where you insert the image after doing Edit > Insert Image, change the "alt text" inside the [] to something the CSS style can refer to and you're done So, (1) looks like : %%html <style>     img[alt=bad_pie]{         float : left;     } </style> And, the cell with the image, when in edit mode, will look like : ![bad_pie](attachment:Capture.PNG) Than...
Post a Comment
Read more

openCV : Really Filtering by Color

The free openCV crash course : img_NZ_bgr = cv.imread('New_Zealand_Lake.jpg', cv.IMREAD_COLOR) b,g,r = cv.split(img_NZ_bgr) plt.figure(figsize=[20,5]) plt.subplot(141);plt.imshow(r, cmap='gray');plt.title("Red") plt.subplot(142);plt.imshow(b, cmap='gray');plt.title("Blue") plt.subplot(143);plt.imshow(g, cmap='gray');plt.title("Green") # merging imgMerged = cv.merge((b,g,r)) # original code : b,g,r plt.subplot(144);plt.imshow(imgMerged[...,::-1]);plt.title("Merged") Gives you : Coolie McVoolie. But, wait a minute! Are you really going to fall for that? Remember those "3D" glasses you got in magazines as a kid that let you see the page in 3D by using filters (each eye sees the picture from the required angle)? Meaning, if you're looking at the Red channel, you want to see : This! Right? How? Easy Make a blank channel (basically using NumPy zeros) Use that blank channel for the filtered channels, ...
Post a Comment
Read more

One Path to Bankruptcy for Replit

User trying to import a module that's not installed. Instead of bumping him and telling her to use a different workspace on which the module *is* installed, use compute resources to try and install.. nuts.. Starting with : from transformers import TFAutoModelForSeq2SeqLM, AutoTokenizer import gradio as gr model = TFAutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small") tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-small") def gen_text(input_string, max_length):     inputs = tokenizer(input_string, return_tensors="pt")     outputs = model.generate(**inputs, max_length=max_length)     final_text = tokenizer.batch_decode(outputs[0], skip_special_tokens=True)     return (final_text) demo = gr.Interface(                                                          fn=gen_text,     ...
Post a Comment
Read more