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import networkx as nx
from node2vec import Node2Vec

G = nx.barbell_graph(m1=7, m2=4)
draw_graph(G, nx.spring_layout(G))

node2vec = Node2Vec(G, dimensions=2)
model = node2vec.fit(window=10)

Computing transition probabilities: 100%
18/18 [00:00<00:00, 261.56it/s]
Generating walks (CPU: 1): 100%|██████████| 10/10 [00:00<00:00, 16.48it/s]

TypeError Traceback (most recent call last)
in ()
6
7 node2vec = Node2Vec(G, dimensions=2)
----> 8 model = node2vec.fit(window=10)

/usr/local/lib/python3.7/dist-packages/node2vec/node2vec.py in fit(self, **skip_gram_params)
186 skip_gram_params['sg'] = 1
187
--> 188 return gensim.models.Word2Vec(self.walks, **skip_gram_params)

TypeError: init() got an unexpected keyword argument 'size'

Hello,

I am using conda. I created a new environment called "new_env" with python=3.7.16 (I had to use an older version of Python because stellargraph was having difficulties with python>3.8) by:

conda create -n new_env python=3.7.16
conda activate new_env

then in the terminal where the new_env being active, I typed:

pip install -r requirements.txt

where the requirements.txt file include the following (from Chapter-3 in the book):

Jupyter==1.0.0
networkx==2.5
matplotlib==3.2.2
karateclub==1.0.19
node2vec==0.3.3
tensorflow==2.4.0
scikit-learn==0.24.0
git+https://github.com/palash1992/GEM.git
git+https://github.com/stellargraph/stellargraph.git

I have two questions.
Question-1: When I run the "01_Shallow_Embeddings.ipynb" notebook given in Chapter-03, for the cell given below, I get the following error in GraphFactorization section:

from gem.embedding.gf import GraphFactorization
G = nx.barbell_graph(m1=10, m2=4)
draw_graph(G)
gf = GraphFactorization(d=2,  data_set=None,max_iter=10000, eta=1*10**-4, regu=1.0)
gf.learn_embedding(G)

Error: ./gf not found. Reverting to Python implementation. Please compile gf, place node2vec in the path and grant executable permission.

Do I go to site_packages in the active conda environment and compile/run a setup.py file in GEM library? Or do I need to clone GEM library (as well as stellar) separate;y rather than putting them in the requirements.txt file, though I thought it is the same procedure.

Question-2: I have also an error when I run the DeepWalk example in the same notebook,
The code:

import networkx as nx
from karateclub.node_embedding.neighbourhood.deepwalk import DeepWalk
G = nx.barbell_graph(m1=10, m2=4)
draw_graph(G)
dw = DeepWalk(dimensions=2)
dw.fit(G)

The error I get:

TypeError                                 Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_22368\195704241.py in <module>
      6 
      7 dw = DeepWalk(dimensions=2)
----> 8 dw.fit(G)

~\anaconda3\envs\gml_book_ch3\lib\site-packages\karateclub\node_embedding\neighbourhood\deepwalk.py in fit(self, graph)
     57                          min_count=self.min_count,
     58                          workers=self.workers,
---> 59                          seed=self.seed)
     60 
     61         num_of_nodes = graph.number_of_nodes()

TypeError: __init__() got an unexpected keyword argument 'iter'

Did anyone have similar issues or know the solution?

Thanks!

Dear authors,

I like your book very much and it helped me get a lot of useful insights, but I have a problem when I do the implementation.

I ran the codes of Graph Classification using GCNs in Chapter04/04_Graph_Neural_Networks.ipynb, but when I try to train the model using the command history = model.fit(
train_gen, epochs=epochs, verbose=1, validation_data=test_gen, shuffle=True,
)

I got an error:
UnimplementedError: Cast string to float is not supported
[[node binary_crossentropy/Cast (defined at :2) ]] [Op:__inference_train_function_2594]

Function call stack:
train_function

It seems like the model used a string, but I'm not very good at python and I'm not able to fix the bug, could you please help me with this? Thank you very much!

I had an issue with numpy and gensim for chapter 3 (first chapter that I ran examples). This was the error specifically:

ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject "gensim"

My solution was to use a conda environment. I set up an environment.yml file as below

name: packt_graphml_env
channels:
   - conda-forge
   - defaults
dependencies:
   - python==3.8.*
   - pip
   - ipykernel
   - pandas
   - gensim==3.8.3
   - numpy==1.19.5
   - networkx==2.5.*
   - matplotlib==3.2.*
   - node2vec==0.3.*
   - karateclub==1.0.*
   - scipy==1.6.*
   - tensorflow==2.4.1
   - scikit-learn==0.24.*
   - stellargraph::stellargraph
   - pip:
     #- "--editable=git+https://github.com/stellargraph/stellargraph.git#egg=stellargraph"
     - "--editable=git+https://github.com/palash1992/GEM.git#egg=GEM"

and install/update with:
mamba env update -f environment.yml

Of course, replace mamba with conda if you don't have mamba. And I added ipykernel for a Jupyter kernel, which was already installed in my base conda environment.

Hope this helps someone.

I tried to run the code "01_Shallow_Embeddings.ipynb" unfortunately when I try to run this excerpt :
from gem.embedding.gf import GraphFactorization

G = nx.barbell_graph(m1=10, m2=4)
draw_graph(G)

gf = GraphFactorization(d=2, data_set=None,max_iter=10000, eta=1*10**-4, regu=1.0)
gf.learn_embedding(G)

I have the following error :
./gf not found. Reverting to Python implementation. Please compile gf, place node2vec in the path and grant executable permission
Iter id: 0, Objective: 95.0097, f1: 95.0035, f2: 0.00623775

The error is located specifically with this instruction: gf.learn_embedding(G)

Hello,
I am trying to execute examples from Graph-Machine-Learning/Chapter07/01_nlp_graph_creation.ipynb in Google Colab.

At line number#5 corpus = pd.DataFrame([..]) I am getting error as :

---------------------------------------------------------------------------
LookupError                               Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/nltk/corpus/util.py in __load(self)
     79             except LookupError as e:
---> 80                 try: root = nltk.data.find('{}/{}'.format(self.subdir, zip_name))
     81                 except LookupError: raise e

5 frames
LookupError: 
**********************************************************************
  Resource reuters not found.
  Please use the NLTK Downloader to obtain the resource:

  >>> import nltk
  >>> nltk.download('reuters')
  
  Searched in:
    - '/root/nltk_data'
    - '/usr/share/nltk_data'
    - '/usr/local/share/nltk_data'
    - '/usr/lib/nltk_data'
    - '/usr/local/lib/nltk_data'
    - '/usr/nltk_data'
    - '/usr/lib/nltk_data'
**********************************************************************


During handling of the above exception, another exception occurred:

LookupError                               Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/nltk/data.py in find(resource_name, paths)
    671     sep = '*' * 70
    672     resource_not_found = '\n%s\n%s\n%s\n' % (sep, msg, sep)
--> 673     raise LookupError(resource_not_found)
    674 
    675 

LookupError: 
**********************************************************************
  Resource reuters not found.
  Please use the NLTK Downloader to obtain the resource:

  >>> import nltk
  >>> nltk.download('reuters')
  
  Searched in:
    - '/root/nltk_data'
    - '/usr/share/nltk_data'
    - '/usr/local/share/nltk_data'
    - '/usr/lib/nltk_data'
    - '/usr/local/lib/nltk_data'
    - '/usr/nltk_data'
    - '/usr/lib/nltk_data'
**********************************************************************

Even after following instructions to nltk.download('reuters') I am still getting the same error. Reuters is download in /root/

~/nltk_data/corpora# ls
reuters.zip

Could you please help me?

Thanks,

follow the code with

`from gem.embedding.gf import GraphFactorization

G = nx.barbell_graph(m1=10, m2=4)
draw_graph(G)

gf = GraphFactorization(d=2, data_set=None,max_iter=10000, eta=1*10**-4, regu=1.0)
gf.learn_embedding(G)`

and got reply

[Errno 13] Permission denied: 'gem/c_exe/gf' ./gf not found. Reverting to Python implementation. Please compile gf, place node2vec in the path and grant executable permission Iter id: 0, Objective: 95.0047, f1: 95.001, f2: 0.00377086

seems there's something I missed?