PALM | use NLP Large-scale Pretraining | Machine Learning library
kandi X-RAY | PALM Summary
kandi X-RAY | PALM Summary
PaddlePALM is a well-designed high-level NLP framework. You can efficiently achieve supervised learning, unsupervised/self-supervised learning, multi-task learning and transfer learning with minor codes based on PaddlePALM. There are three layers in PaddlePALM architecture, i.e., component layer, trainer layer and high-level trainer layer from bottom to top. In component layer, PaddlePALM supplies 6 decoupled components to achieve a NLP task. Each component contains rich pre-defined classes and a Base class. Pre-defined classes are aiming at typical NLP tasks, and the base class is to help users develop a new Class (based on pre-defined ones or from the base). The trainer layer is to establish a computation graph with selected components and do training and predicting. The training strategy, model saving and loading, evaluation and predicting procedures are described in this layer. Noted a trainer can only process one task. The high-level trainer layer is for complicated learning and inference strategy, e.g., multi-task learning. You can add auxilary tasks to train robust NLP models (improve test set and out-of-domain performance of a model), or jointly training multiple related tasks to gain more performance for each task. | module | illustration | | - | - | | paddlepalm | an open source NLP pretraining and multitask learning framework, built on paddlepaddle. | | paddlepalm.reader | a collection of elastic task-specific dataset readers. | | paddlepalm.backbone | a collection of classic NLP representation models, e.g., BERT, ERNIE, RoBERTa. | | paddlepalm.head | a collection of task-specific output layers. | | paddlepalm.lr_sched | a collection of learning rate schedualers. | | paddlepalm.optimizer | a collection of optimizers. | | paddlepalm.downloader | a download module for pretrained models with configure and vocab files. | | paddlepalm.Trainer | the core unit to start a single task training/predicting session. A trainer is to build computation graph, manage training and evaluation process, achieve model/checkpoint saving and pretrain_model/checkpoint loading.| | paddlepalm.MultiHeadTrainer | the core unit to start a multi-task training/predicting session. A MultiHeadTrainer is built based on several Trainers. Beyond the inheritance of Trainer, it additionally achieves model backbone reuse across tasks, trainer sampling for multi-task learning, and multi-head inference for effective evaluation and prediction. |.
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Top functions reviewed by kandi - BETA
- Builds the graph
- Multi - layer encoder
- Multihead attention layer
- Multi - head layer layer
- Creates a function that creates a joint iterator over the given iterators
- Ensures that the shape of the dtype is consistent with attr
- Create a batch of zeros from attrs
- Create the forward computation
- Builds the head
- Saves the model
- Builds the gradients
- Tokenize Chinese characters
- Runs the prediction
- Train the model
- Creates a inference function for multiple inputs
- Pre - process layer normalization layer
- Create a function that returns a function that creates a multihead iterator
- Load checkpoint into train program
- Evaluate res_eval
- Builds the model
- Fit readers with mixing ratio
- Creates the prediction forward for the prediction
- Merge training readers
- Prepare batch data
- Generate data generator
- Tokenize text
PALM Key Features
PALM Examples and Code Snippets
Lines of Code : 12
License : No License
Copyconst functions = (obj, inherited = false) =>
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function Foo() {
this.a = () => def capitalize(s, lower_rest = False):
return ''.join([s[:1].upper(), (s[1:].lower() if lower_rest else s[1:])])
capitalize('fooBar') # 'FooBar'
capitalize('fooBar', True) # 'Foobar'
Community Discussions
Trending Discussions on PALM
QUESTION
I am using laravel framework to check if it mobile using helper.php, but i get sometimes errors in laravel.log with: Undefined index: HTTP_USER_AGENT
My Code helper.php code:
...ANSWER
Answered 2021-Jun-14 at 05:54It is because, there is no case if it is NULL for HTTP_USER_AGENT you can modify:
QUESTION
Here's the data I need to fix:
...ANSWER
Answered 2021-May-27 at 21:17I almost agree with @anubhava: (?
I believe the OP wanted to exclude the ; character from the match but not the newlines.
QUESTION
I've created a mixed model in Keras, creating weights for metadata and image data and then combining them for the classification. Here's the model:
ANSWER
Answered 2021-May-16 at 20:43This is not a direct answer, but will help to solve the question. There is missing information to solve your problem.
BUT first: the most obvious problem is; you provide meta_train which is a pandas data frame. Convert it to an array. Please try this first.
Second, if you still have problem, then model.fit may not handle a list [meta_train, flow], then you may have to find a way to provide two inputs to be handled by your model.
For that, you should provide the followings as MRE in order to reproduce your problem.
(1) Your code for the model even though one may generate same model based on the summary provided.
(2) the shape of y_train.
QUESTION
Had this commit yesterday where the process would go straight to Heroku's memory limit giving me an R15 error - It worked really well in my testing and also on heroku until it gets to a random number of checked items, at which it throws the error. The interesting part is that right after the error, i get another R15 one, which says i am using only 22.2% of available memory.
Here is the code giving me the error:
...ANSWER
Answered 2021-Apr-23 at 10:27Apparently, denying javascript requests was the solution to this - even though it's not perfect and some sites may require javascript to run, this one was the exception. Just update the config function (which I forgot to include) that blocked images and css, to block js as well.
Here is how that function looks now
QUESTION
I am trying to render a Component and getting error collections.map is not a function. below is the attached file of my SHOP_DATA and CollectionOverview. I am importing data from the SHOP_DATA file and in other components it's working fine. I am also getting error like Cannot read property 'toUpperCase' of undefined.
...ANSWER
Answered 2021-Apr-20 at 17:00map function is not native to objects. It is used to iterate an array and it also returns an array, and you are using it on objects. This is the correct implementation.
QUESTION
I've been staring at this for most of the afternoon and am stumped. The problem seems so simple that I'm sure it will be a real Doh! face palm moment when I crack it.
Some background:
I'm creating a little project to use an Arduino to read in Infrared signals from my remote controllers and send them to a Python program I'm writing.
I send the sample command to the Arduino as a JSON string and use the Arduinojson library to deserialise it. That works fine. My sampling method captures the signal and writes it to an int array.
Where I'm struggling is converting that array to a JSON string. I tried using the same library for serialising it but it used a lot of memory, so I'm trying to write a loop to convert the ints to string form and construct a JSON string manually from them.
My signal capture method:
...ANSWER
Answered 2021-Apr-17 at 17:34Your code
QUESTION
Consider the following pandas dataframe:
this is an example of ingredients_text :
farine de blé 34% (france), pépites de chocolat 20g (ue) (sucre, pâte de cacao, beurre de cacao, émulsifiant lécithines (tournesol), arôme) (cacao : 44% minimum), matière grasse végétale (palme), sucre, 8,5% chocolat(sucre, pâte de cacao, cacao et cacao maigre en poudre) (cacao: 38% minimum), 5,5% éclats de noix de pécan (non ue), poudres à lever : diphosphates carbonates de sodium, blancs d’œufs, fibres d'acacia, lactose et protéines de lait, sel. dont lait.
oignon 18g oil hell: kartoffelstirke, milchzucker, maltodextrin, reismehl. 100g produkt enthalten: 1559KJ ,energie 369 kcal lt;0.5g lt;0.1g 909 fett davon gesättigte fettsāuren kohlenhydrate davon ,zucker 26g
I separated the ingredients of each line into words with the folowing code :
...ANSWER
Answered 2021-Apr-16 at 14:52df = pd.DataFrame({'ingredient_text': ['a%bgC, abc, a%, cg', 'xyx']})
ingredient_text
0 a%bgC, abc, a%, cg
1 xyx
QUESTION
I am trying to find SPQR tree of my graph, so I find out that sage can help me. I put my code here https://sagecell.sagemath.org/ (and than in sage programe). Here it is:
...ANSWER
Answered 2021-Apr-06 at 23:44An SPQR tree can only be formed for biconnected graphs. These are connected graphs that stay connected even if any node in the graph is deleted. A graph is not biconnected if it has an articulation vertex (also called a cut vertex), a node that, if removed, leaves the graph disconnected.
The error you're getting indicates that your graph has at least one cut vertex, so it's not possible to form the SPQR tree.
QUESTION
Below is a string I've tried to explode only on comma's outside of the first set of brackets.
Wheat Flour (2%) [Wheat Flour, Wheat Gluten, Calcium Carbonate, Iron, Niacin (B3), Thiamin (B1), Ascorbic Acid], Water, Yeast, Salt, Vegetable Oils (Palm, Rapeseed, oils (sunflower, rapeseed)), Soya Flour
ANSWER
Answered 2021-Apr-06 at 10:03You can use
QUESTION
I have a column named "Trip", in which I have infos such as the hotel, country, and type of trip. The thing is these infos are hand typed, so sometimes instead of typing "HOTEL ABC", the person entering the infos simply enters "ABC", or event "HTL ABC". Also, ABC can also refer to a country.
What I want is to extract all hotel names on each cell. Here's the function I created, but I can't get it to work. (Y2 is the TRIP Column)
...ANSWER
Answered 2021-Mar-26 at 18:47- You are missing semicolons before "CORAIL NOIR" and "LOHARANO" .
- You need to remove the final semicolon after "FRIDAY ATTITUDE" because
IFS expects all arguments after position 0 to be in pairsand the final semicolon makes Google Sheets think another set of arguments is coming. - You can help yourself out with future troubleshooting by spacing out your function better - eg the following will still work when pasted into Google Sheets:
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