python-3.5

I've built a binary classifier using Tensorflow and now I would like to evaluate the classifier using AUC and accuracy. As far as accuracy is concerned, I can easily do like this: X = tf.placeholder('float', [None, n_input]) y = tf.placeholder('float', [None, n_classes]) pred = mlp(X, weights, biases, dropout_keep_prob) correct_prediction = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1)) accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float")) When calculating AUC I use the following: print(tf.argmax(pred, 1).dtype.name) print(tf.argmax(pred, 1).dtype.name) a = tf.cast(tf.argmax(pred, 1)

Suppose I have a function: def get_some_date(some_argument: int=None) -> %datetime_or_None%: if some_argument is not None and some_argument == 1: return datetime.utcnow() else: return None How do I specify the return type for something that can be None ? You're looking for Optional . Since your return type can either be datetime (as returned from datetime.utcnow() ) or None you should use Optional[datetime] : from typing import Optional def get_some_date(some_argument: int=None) -> Optional[datetime]: # as defined From the documentation on typing, Optional is shorthand for: Optional[X] is

I've read tons of articles and tutorial about Python's 3.5 async/await thing. I have to say I'm pretty confused, because some use get_event_loop() and run_until_complete(), some use ensure_future(), some use asyncio.wait(), and some use call_soon(). It seems like I have a lot choices, but I have no idea if they are completely identical or there are cases where you use loops and there are cases where you use wait(). But the thing is all examples work with asyncio.sleep() as simulation of real slow operation which returns an awaitable object. Once I try to swap this line for some real code the

Let's say we have a dummy function: async def foo(arg): result = await some_remote_call(arg) return result.upper() What's the difference between: coros = [] for i in range(5): coros.append(foo(i)) loop = get_event_loop() loop.run_until_complete(wait(coros)) And: from asyncio import ensure_future futures = [] for i in range(5): futures.append(ensure_future(foo(i))) loop = get_event_loop() loop.run_until_complete(wait(futures)) Note : The example returns a result, but this isn't the focus of the question. When return value matters, use gather() instead of wait() . Regardless of return value, I'm

I have a generator of tuples and I need to delete tuples containing same elements. I need this output for iterating. Input = ((1, 1), (1, 2), (1, 3), (3, 1), (3, 2), (3, 3)) Output= ((1, 1), (1, 2), (1, 3)) Order of output doesn't matter. I have checked this question but it is about lists: Delete duplicate tuples with same elements in nested list Python I use generators to achieve fastest results as the data is very large. You can normalize the data by sorting it, then add it to a set to remove duplicates >>> Input = ((1, 1), (1, 2), (1, 3), (3, 1), (3, 2), (3, 3)) >>> Output = set(tuple

I'm trying to replace a string which will be in the form of path='/users/username/folder' in a text file. I'm reading that text file and searching the line which starts from 'path ='. Here I've two problems, I'm unable to replace that line using following code If that string starts in between then this code may not work as I'm checking line.startswith(). Please help. f = open('/Volumes/Personal/example.text','r+') for line in f: print(line, end='') if (line.startswith("path = ")): # You need to include a newline if you're replacing the whole line line = CurrentFilePath + "\n" f.write(line)