prefetch | Customizable interaction-based link prefetching
kandi X-RAY | prefetch Summary
kandi X-RAY | prefetch Summary
Customizable interaction-based link prefetching based largely on InstantcClick.
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QUESTION
I have created a Django REST Framework endpoint that returns all the data I need for my page. I am trying to call this endpoint in one of my views and pass the response to the html template as part of the render.
when I print(response) it returns . All nothing is returned when I use {{ response.name }} in the html template. What am I missing here?
urls.py
...ANSWER
Answered 2021-Jun-13 at 12:13response = SetsIndividualData.as_view()(request)
print(response)
QUESTION
Why does Python not allow a comment after a line continuation "\" character, is it a technical or stylistic requirement?
According to the docs (2.1.5):
A line ending in a backslash cannot carry a comment.
and (2.1.3):
A comment signifies the end of the logical line unless the implicit line joining rules are invoked. Comments are ignored by the syntax.
PEP 8 does discourage inline comments so I can see how this may stylistically be "unpythonic." I could also see how the "\" could be ambiguous if it allowed comments (should the interpreter ignore all subsequent tokens or just comments?) but I think a distinction could easily be made.
Coming from Javascript and accustomed to the fluid interface style, I prefer writing chains like the following instead of reassignment:
...ANSWER
Answered 2021-Jun-09 at 21:48For the same reason you can't have whitespace after the backslash. It simplifies the parsing, as it can simply remove any backslash-newline pairs before doing any more parsing. If there were spaces or comments after the backslash, there's no backslash-newline sequence to remove.
QUESTION
I have a TF dataset
...ANSWER
Answered 2021-Jun-08 at 12:32You could use tf.data.Dataset.shard.
Creates a Dataset that includes only 1/num_shards of this dataset.
shard is deterministic. The Dataset produced by A.shard(n, i) will contain all elements of A whose index mod n = i.
QUESTION
A snippet of my package.json
...ANSWER
Answered 2021-Jun-08 at 05:39I was able to add the preload Webpack plugin by putting it in the configureWebpack object, instead of the chainWebpack object.
So the configureWebpack object would look like this:
QUESTION
I have error I want help for it please help me
...the error ;
ANSWER
Answered 2021-Jun-05 at 18:22I modified some things in the code but never got the saame error as you. This code works for me and even with the exact link of your video :
QUESTION
I am currently doing an assignment for a class that requires me to develop a Maven project on eclipse that utilizes Dropwizard Authentication and Jersey HTTP. I looked everywhere on the internet for a solution, including stackoverflow. When I run the server on my local machine, it seems to run fine. But when I do the simple health check on http://localhost:8080/status, it gives me this error message.
...ANSWER
Answered 2021-Jun-06 at 00:15This is a serialization issue. As per the github repo that you shared there doesn't seem to be a endpoint associated with /gameusers path. But its being called in the health check callback. So the call is failing and its not able to deserialize error response into ArrayList. In GameUserRESTController.java you need to add the path as follows:
QUESTION
From: next/link
You can see that the component from next/link enables client-side transitions and link prefetching, which are great features, but maybe not for all cases.
Please see the caveat I've run into. Let's say I have the following pages:
Home- Some landing page with a nav barLatest- Here I can see my latest postsAdmin- Here I can add more posts
The Latest page from the example above uses getStaticProps with revalidate. Something like:
ANSWER
Answered 2021-Jun-05 at 17:23I've posted this very same question in several forums and this is the response I've got:
It seems what you described is true.
next/linkcaches results in the client-side and your visitor will not fetch a revalidated result out of the box unless there is a full-page reload.Depending on the likelihood of content changes, you might want to use
instead or you can look at some client-side content reload strategy that kicks in after mount and query data source for updated content.
Given that fact, I'll stick to using next/link and client-side transitions. But I'll also use something like a setInterval() to do a full website reload from time to time, so I'm sure my users will keep getting revalidated pages eventually.
QUESTION
I want to include in my WordPress page mydomain.com/plan which is page_id = 25 :
...ANSWER
Answered 2021-Jun-01 at 07:21Yes, prefetching will still work.
It will also improve the page loading performance a little bit because prefetching will start already halfway into the loading of the page if it is in the head.
Moving it to the bottom of the , it will only start after all the important stuff is done.
QUESTION
IMAGE_RES = 224
def format_image(image, label):
image = tf.image.resize(image, (IMAGE_RES, IMAGE_RES))/255.0
return image, label
BATCH_SIZE = 32
train_batches = train_dataset.map(format_image).batch(BATCH_SIZE).prefetch(1)
train_gray_batches = train_grey_dataset.map(format_image).batch(BATCH_SIZE).prefetch(1)
test_batches = test_dataset.map(format_image).batch(BATCH_SIZE).prefetch(1)
test_grey_batches = test_grey_dataset.map(format_image).batch(BATCH_SIZE).prefetch(1)
----------
threshold = 100.0
dropoutrate = 0.5
n_outchannels = 3
height, width = IMAGE_RES, IMAGE_RES
def max_norm_regularizer(threshold, axes=None, name="max_norm",
collection="max_norm"):
def max_norm(weights):
clipped = tf.clip_by_norm(weights, clip_norm=threshold, axes=axes)
clip_weights = tf.assign(weights, clipped, name=name)
tf.add_to_collection(collection, clip_weights)
return None # there is no regularization loss term
return max_norm
max_norm_reg = max_norm_regularizer(threshold=threshold)
clip_all_weights = tf.compat.v1.get_collection("max_norm")
----------
def leaky_relu(z,name=None):
return tf.maximum(0.5*z,z,name=name)
from functools import partial
he_init = tf.keras.initializers.VarianceScaling()
----------
X = tf.compat.v1.placeholder(shape=(None,width,height,2),dtype=tf.float32)
print(X)
training = tf.compat.v1.placeholder_with_default(False,shape=(),name='training')
X_drop = tf.keras.layers.Dropout(X,dropoutrate)
my_batch_norm_layer = partial(tf.keras.layers.BatchNormalization,training=training,momentum=0.9)
bn0 = my_batch_norm_layer(X_drop)
bn0_act = leaky_relu(bn0)
print(bn0_act)
ANSWER
Answered 2021-May-29 at 22:52You need to put the arguments inside brackets since the training keyword is currently being applied to partial(). You also want to use trainable instead of training (I'm assuming you want to freeze the batchnorm layer).
QUESTION
I have seem some examples of how to prefetch_related fields in a forward and backward relationship in Django, but I have doubts about how can this be applied if we want to prefetch all the fields of a related model.
For instance if I want to fetch all content from the following models, using HealthCheck as the starting point. Which would be the most optimized query to achieve that?
...ANSWER
Answered 2021-May-28 at 06:36It should be possible with:
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