inception | Hands-off auto-configuration tools for android devices | Android library
kandi X-RAY | inception Summary
kandi X-RAY | inception Summary
Hands-off auto-configuration tools for android devices
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Top functions reviewed by kandi - BETA
- Parse the code
- Applies a diff to the config dict
- Set the output path
- Returns the out path of this exception
- Parses the config and creates a new config directory
- Create all required directories
- Create a directory
- Sets up the directory paths
- Parses the command line arguments
- Process configuration files
- Compares the mount points
- Make maker
- Make the Inception
- Process command line arguments
- Make the image
- Process the code
- Make the recovery image
- Make a boot image
- Make an update package
- This method parses the parsed arguments
- Make the installer
- Make a cache image
- Create a new configuration
- Generate the script
- Make the images
- Process plant arguments
inception Key Features
inception Examples and Code Snippets
Community Discussions
Trending Discussions on inception
QUESTION
I've a spring boot application which run sql on H2 to create database table during startup. The project is in github here.
I've Entity called Movie.java
The sql that I'm running is below and on github here -
...ANSWER
Answered 2022-Apr-03 at 09:39The main problem is probably "movie"
as table-name incl the "
So this should work
schema.sql:
QUESTION
I have a table that looks like the following:
...ANSWER
Answered 2022-Mar-29 at 03:27You can use str format for the query
QUESTION
The following source code could get both probabilities and logits from an imagenet pretrained model in Tensorflow
...ANSWER
Answered 2022-Mar-21 at 12:55IIUC, you should be able to do this directly the same way:
QUESTION
I have trained a pretrained ResNet18 model with my custom dataset on Pytorch and wondered whether I could transfer my model file to train another one with a different architecture, e.g. ResNet50. I know I have to save my model accordingly (explained well on another post here) but this was a question that I have never thought before.
I was planning to use more advanced models like VisionTransformers (ViT) but I couldn't figure out whether I had to start with a pretrained ViT already or I could just take my previous model file and use it as the pretrained model to train a ViT.
Example Scenario: ResNet18 --> ResNet50 --> Inception v3 --> ViT
My best guess it that it's not possible due to number of weights, neurons and layer structures but I would love to hear that if I miss a crucial point here.
Thanks!
ANSWER
Answered 2022-Mar-15 at 08:56Between models that only differ in number of layers (Resnet-18 and Resnet-50), it has been done to initialize some layers of the larger model from the weights of the smaller model's layers. Inversely, you can truncate a larger model by taking a subset of regularly spaced layers and initialize a smaller model. In both cases, you need to retrain everything at the end if you hope to achieve semi-decent performances.
The whole point of using architectures that vastly differ (vision transformers vs CNNs) is to learn different features from the inputs and unlock new levels of semantic understanding. Recent models like BeiT also use new self-supervised training schemes that have nothing to do with the classic ImageNet pretraining. Using trained weights from another model would go against the point.
Having said that,if you want to use a ViT, why not start from the available pretrained weights on HuggingFace and fine-tune it on the data you used to train your ResNet50 ?
QUESTION
Given the following DataFrame -
json_path Reporting Group Entity/Grouping Entity ID Adjusted Value (Today, No Div, USD) Adjusted TWR (Current Quarter, No Div, USD) Adjusted TWR (YTD, No Div, USD) Annualized Adjusted TWR (Since Inception, No Div, USD) Adjusted Value (No Div, USD) TWR Audit Note data.attributes.total.children.[0].children.[0].children.[0] Barrack Family William and Rupert Trust 9957007 -1.44 -1.44 data.attributes.total.children.[0].children.[0].children.[0].children.[0] Barrack Family Cash - -1.44 -1.44 data.attributes.total.children.[0].children.[0].children.[1] Barrack Family Gratia Holdings No. 2 LLC 8413655 55491732.66 -0.971018847 -0.971018847 11.52490309 55491732.66 data.attributes.total.children.[0].children.[0].children.[1].children.[0] Barrack Family Investment Grade Fixed Income - 18469768.6 18469768.6 data.attributes.total.children.[0].children.[0].children.[1].children.[1] Barrack Family High Yield Fixed Income - 3668982.44 -0.205356545 -0.205356545 4.441190127 3668982.44The following code should filter out rows where rows != 'Cash' (Entity/Grouping
column) and that have a blank value in either Adjusted TWR (Current Quarter, No Div, USD)
column, Adjusted TWR (YTD, No Div, USD)
column or Annualized Adjusted TWR (Since Inception, No Div, USD)
column.
Code: The following code expects to achieve this -
...ANSWER
Answered 2022-Mar-07 at 20:47return reporting_group_df, unknown_df, perf_asset_class_df, perf_entity_df, perf_entity_group_df
QUESTION
Given the following pandas DataFrame -
json_path Reporting Group Entity/Grouping Entity ID Adjusted Value (Today, No Div, USD) Adjusted TWR (Current Quarter, No Div, USD) Adjusted TWR (YTD, No Div, USD) Annualized Adjusted TWR (Since Inception, No Div, USD) Adjusted Value (No Div, USD) TWR Audit Note data.attributes.total.children.[0].children.[0].children.[0] Barrack Family William and Rupert Trust 9957007 -1.44 -1.44 data.attributes.total.children.[0].children.[0].children.[0].children.[0] Barrack Family Cash - -1.44 -1.44 data.attributes.total.children.[0].children.[0].children.[1] Barrack Family Gratia Holdings No. 2 LLC 8413655 55491732.66 -0.971018847 -0.971018847 11.52490309 55491732.66 data.attributes.total.children.[0].children.[0].children.[1].children.[0] Barrack Family Investment Grade Fixed Income - 18469768.6 18469768.6 data.attributes.total.children.[0].children.[0].children.[1].children.[1] Barrack Family High Yield Fixed Income - 3668982.44 -0.205356545 -0.205356545 4.441190127 3668982.44I am trying to filter on rows that != Cash
('Entity/Grouping'
column) and that have a blank value in 'Adjusted TWR (Current Quarter, No Div, USD)'
column, 'Adjusted TWR (YTD, No Div, USD)'
column or 'Annualized Adjusted TWR (Since Inception, No Div, USD)'
column.
Code: I am trying to achieve this by the following code -
ANSWER
Answered 2022-Mar-07 at 05:43Use |
, not or
to combine boolean Series.
In your case you can simplify using comparison to empty string on a slice of all target columns and any
:
QUESTION
Given the following pandas DataFrame -
json_path Reporting Group Entity/Grouping Entity ID Adjusted Value (Today, No Div, USD) Adjusted TWR (Current Quarter, No Div, USD) Adjusted TWR (YTD, No Div, USD) Annualized Adjusted TWR (Since Inception, No Div, USD) Adjusted Value (No Div, USD) TWR Audit Note data.attributes.total.children.[0].children.[0].children.[0] Barrack Family William and Rupert Trust 9957007 -1.44 -1.44 data.attributes.total.children.[0].children.[0].children.[0].children.[0] Barrack Family Cash - -1.44 -1.44 data.attributes.total.children.[0].children.[0].children.[1] Barrack Family Gratia Holdings No. 2 LLC 8413655 55491732.66 -0.971018847 -0.971018847 11.52490309 55491732.66 data.attributes.total.children.[0].children.[0].children.[1].children.[0] Barrack Family Investment Grade Fixed Income - 18469768.6 18469768.6 data.attributes.total.children.[0].children.[0].children.[1].children.[1] Barrack Family High Yield Fixed Income - 3668982.44 -0.205356545 -0.205356545 4.441190127 3668982.44I try and save only rows that contain 4x occurances of .children.[]
using the following statement -
Code: perf_by_entity_df = df[df['json_path'].str.contains(r'(\.children\.\[\d+\]){4}')]
However receive the following:
Error:UserWarning: This pattern is interpreted as a regular expression, and has match groups. To actually get the groups, use str.extract.
Any suggestions why this is happening?
...ANSWER
Answered 2022-Mar-06 at 21:25Use the code below to suppress the warning:
QUESTION
Output: User Ruby watched Transit and Max also watched the same movie and gave rating above 3. So User ruby recommendation has to be Max Jurassic Park and not weekend away userRecommend("Ruby", ratings) => ["Jurassic Park"]
How do i get the ouput for below?
...ANSWER
Answered 2022-Mar-05 at 17:37You could collect all user/movie and movie/user relations in two hash tables and get the users who have rated the same movie.
The get from the users the other movies, take only unique movies and filter the rated out.
QUESTION
I am trying to deploy a smart contract via Remix. Unfortunately, it fails with a very unhelpful error message.
Error MessageCodecreation of MyContract errored: Error encoding arguments: Error: invalid arrayify value (argument="value", value="", code=INVALID_ARGUMENT, version=bytes/5.5.0)
Here is the constructor the contract
uses:
ANSWER
Answered 2022-Feb-08 at 18:12The constructor takes a byte array as an argument.
When you pass an empty value, it results in the error message mentioned in your question. It's because you're effectively passing "no value" - not "empty byte array".
creation of MyContract errored: Error encoding arguments: Error: invalid arrayify value (argument="value", value="", code=INVALID_ARGUMENT, version=bytes/5.5.0)
If you want to pass an empty byte array, you need to use the []
or 0x
expression (both options work):
QUESTION
Background: I am trying to normalize a json file, and save into a pandas dataframe, however I am having issues navigating the json structure and my code isn't working as expected.
Expected dataframe output: Given the following example json
file (uses randomized data, but exactly the same format as the real one), this is the output I am trying to produce -
(1/31/2022, No Div, USD) Adjusted TWR
(Current Quarter No Div, USD)) Adjusted TWR
(YTD, No Div, USD) Annualized Adjusted TWR
(Since Inception, No Div, USD) Inception Date Risk Target Portfolio_1 $260,786 (44.55%) (44.55%) (44.55%) * Apr 7, 2021 N/A The FW Irrev Family Tr 9552252 $260,786 0.00% 0.00% 0.00% * Jan 11, 2022 N/A Portfolio_2 $18,396,664 (5.78%) (5.78%) (5.47%) * Sep 3, 2021 Growth FW DAF 10946585 $18,396,664 (5.78%) (5.78%) (5.47%) * Sep 3, 2021 Growth Portfolio_3 $60,143,818 (4.42%) (4.42%) 7.75% * Dec 17, 2020 - The FW Family Trust 13014080 $475,356 (6.10%) (6.10%) (3.97%) * Apr 9, 2021 Aggressive FW Liquid Fund LP 13396796 $52,899,527 (4.15%) (4.15%) (4.15%) * Dec 30, 2021 Aggressive FW Holdings No. 2 LLC 8413655 $6,768,937 (0.77%) (0.77%) 11.84% * Mar 5, 2021 N/A FW and FR Joint 9957007 ($1) - - - * Dec 21, 2021 N/A
Actual dataframe output: despite my best efforts, I have only been able to get bolded rows to map into the dataframe:
New Entity Group Entity ID Adjusted Value(1/31/2022, No Div, USD) Adjusted TWR
(Current Quarter No Div, USD)) Adjusted TWR
(YTD, No Div, USD) Annualized Adjusted TWR
(Since Inception, No Div, USD) Inception Date Risk Target Portfolio_1 $260,786 (44.55%) (44.55%) (44.55%) * Apr 7, 2021 N/A Portfolio_2 $18,396,664 (5.78%) (5.78%) (5.47%) * Sep 3, 2021 Growth Portfolio_3 $60,143,818 (4.42%) (4.42%) 7.75% * Dec 17, 2020 -
JSON file: this is the file I am trying to normalize and map into a dataframe:
...ANSWER
Answered 2022-Feb-04 at 15:02Since your children
's children
has same structure as children
, you can try using json_normalize
twice separately and append it together.
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Vulnerabilities
No vulnerabilities reported
Install inception
You can use inception like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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