'Variable type field must be a TensorType.' error when running cell2location

Hi,

I’ve followed the tutorial, however I’m stack during the last part of 2/3. When I run the code above, I get an error.

os.environ["THEANO_FLAGS"] = 'device=cpu,floatX=float32,openmp=True,force_device=True'
r = cell2location.run_cell2location(

      # Single cell reference signatures as pd.DataFrame
      # (could also be data as anndata object for estimating signatures
      #  as cluster average expression - `sc_data=adata_snrna_raw`)
      sc_data=inf_aver,
      # Spatial data as anndata object
      sp_data=adata_vis,

      # the column in sc_data.obs that gives cluster idenitity of each cell
      summ_sc_data_args={'cluster_col': "TaxonomyRank4",
                         # select marker genes of cell types by specificity of their expression signatures
                         'selection': "cluster_specificity",
                         # specificity cutoff (1 = max, 0 = min)
                         'selection_specificity': 0.5
                        },

      train_args={'use_raw': True, # By default uses raw slots in both of the input datasets.
                  'n_iter': 40000, # Increase the number of iterations if needed (see QC below)

                  # Whe analysing the data that contains multiple experiments,
                  # cell2location automatically enters the mode which pools information across experiments
                  'sample_name_col': 'sample'}, # Column in sp_data.obs with experiment ID (see above)


      export_args={'path': data_dir + 'cell2location_model/'
                  }

)

And the error what I get is:

### Summarising single cell clusters ###
### Creating model ### - time 0.0 min
Traceback (most recent call last):
  File "run_cell2location.py", line 191, in <module>
    export_args={'path': data_dir + 'cell2location_model/'
  File "/home/tsztank/miniconda3/envs/cellpymc/lib/python3.7/site-packages/cell2location/run_c2l.py", line 345, in run_cell2location
    **model_kwargs)
  File "/home/tsztank/miniconda3/envs/cellpymc/lib/python3.7/site-packages/cell2location/models/LocationModelLinearDependentWMultiExperiment.py", line 278, in __init__
    total_size=self.X_data.shape)
  File "/home/tsztank/miniconda3/envs/cellpymc/lib/python3.7/site-packages/pymc3/distributions/distribution.py", line 83, in __new__
    return model.Var(name, dist, data, total_size, dims=dims)
  File "/home/tsztank/miniconda3/envs/cellpymc/lib/python3.7/site-packages/pymc3/model.py", line 1117, in Var
    model=self,
  File "/home/tsztank/miniconda3/envs/cellpymc/lib/python3.7/site-packages/pymc3/model.py", line 1737, in __init__
    data = as_tensor(data, name, model, distribution)
  File "/home/tsztank/miniconda3/envs/cellpymc/lib/python3.7/site-packages/pymc3/model.py", line 1691, in as_tensor
    data = tt.as_tensor_variable(data, name=name)
  File "/home/tsztank/miniconda3/envs/cellpymc/lib/python3.7/site-packages/theano/tensor/basic.py", line 158, in as_tensor_variable
    "Variable type field must be a TensorType.", x, x.type)
theano.tensor.var.AsTensorError: ('Variable type field must be a TensorType.', SparseVariable{csr,int16}, Sparse[int16, csr])

[lopollar]

Hi, I am trying to run through th whole tutorial of cell2location on the data provided by the tutorial before trying it on my own data. I however, encounter problems when arriving at running the actual model. when running:

sc.settings.set_figure_params(dpi = 100, color_map = 'viridis', dpi_save = 100,
                              vector_friendly = True, format = 'pdf',
                              facecolor='white')

r = cell2location.run_cell2location(

      # Single cell reference signatures as pd.DataFrame
      # (could also be data as anndata object for estimating signatures
      #  as cluster average expression - `sc_data=adata_snrna_raw`)
      sc_data=inf_aver,
      # Spatial data as anndata object
      sp_data=adata_vis,

      # the column in sc_data.obs that gives cluster idenitity of each cell
      summ_sc_data_args={'cluster_col': "annotation_1",
                         # select marker genes of cell types by specificity of their expression signatures
                         'selection': "cluster_specificity",
                         # specificity cutoff (1 = max, 0 = min)
                         'selection_specificity': 0.07
                        },

      train_args={'use_raw': True, # By default uses raw slots in both of the input datasets.
                  'n_iter': 40000, # Increase the number of iterations if needed (see QC below)

                  # Whe analysing the data that contains multiple experiments,
                  # cell2location automatically enters the mode which pools information across experiments
                  'sample_name_col': 'sample'}, # Column in sp_data.obs with experiment ID (see above)


      export_args={'path': results_folder, # path where to save results
                   'run_name_suffix': '' # optinal suffix to modify the name the run
                  },

      model_kwargs={ # Prior on the number of cells, cell types and co-located groups

                    'cell_number_prior': {
                        # - N - the expected number of cells per location:
                        'cells_per_spot': 8,
                        # - A - the expected number of cell types per location:
                        'factors_per_spot': 9,
                        # - Y - the expected number of co-located cell type groups per location
                        'combs_per_spot': 5
                    },

                     # Prior beliefs on the sensitivity of spatial technology:
                    'gene_level_prior':{
                        # Prior on the mean
                        'mean': 1/2,
                        # Prior on standard deviation,
                        # a good choice of this value should be at least 2 times lower that the mean
                        'sd': 1/4
                    }
      }
)

I encounter following error, the same type as mentioned above:

---------------------------------------------------------------------------
AsTensorError                             Traceback (most recent call last)
<ipython-input-28-5578f54fa95f> in <module>
     49                         # Prior on standard deviation,
     50                         # a good choice of this value should be at least 2 times lower that the mean
---> 51                         'sd': 1/4
     52                     }
     53       }

/srv/scratch/lottep/anaconda3/envs/cellpymc2/lib/python3.7/site-packages/cell2location/run_c2l.py in run_cell2location(sc_data, sp_data, model_name, verbose, show_locations, return_all, summ_sc_data_args, train_args, model_kwargs, posterior_args, export_args)
    343                 fact_names=fact_names,
    344                 sample_id=sp_data.obs[train_args['sample_name_col']],
--> 345                 **model_kwargs)
    346 
    347     ####### Print run name #######

/srv/scratch/lottep/anaconda3/envs/cellpymc2/lib/python3.7/site-packages/cell2location/models/LocationModelLinearDependentWMultiExperiment.py in __init__(self, cell_state_mat, X_data, n_comb, data_type, n_iter, learning_rate, total_grad_norm_constraint, verbose, var_names, var_names_read, obs_names, fact_names, sample_id, gene_level_prior, gene_level_var_prior, cell_number_prior, cell_number_var_prior, phi_hyp_prior, spot_fact_mean_var_ratio, exper_gene_level_mean_var_ratio)
    276                                                                      1 / tt.pow(self.gene_E, 2)),
    277                                                    observed=self.x_data,
--> 278                                                    total_size=self.X_data.shape)
    279 
    280             # =====================Compute nUMI from each factor in spots  ======================= #

/srv/scratch/lottep/anaconda3/envs/cellpymc2/lib/python3.7/site-packages/pymc3/distributions/distribution.py in __new__(cls, name, *args, **kwargs)
     81         else:
     82             dist = cls.dist(*args, **kwargs)
---> 83         return model.Var(name, dist, data, total_size, dims=dims)
     84 
     85     def __getnewargs__(self):

/srv/scratch/lottep/anaconda3/envs/cellpymc2/lib/python3.7/site-packages/pymc3/model.py in Var(self, name, dist, data, total_size, dims)
   1115                     distribution=dist,
   1116                     total_size=total_size,
-> 1117                     model=self,
   1118                 )
   1119             self.observed_RVs.append(var)

/srv/scratch/lottep/anaconda3/envs/cellpymc2/lib/python3.7/site-packages/pymc3/model.py in __init__(self, type, owner, index, name, data, distribution, total_size, model)
   1735 
   1736         if distribution is not None:
-> 1737             data = as_tensor(data, name, model, distribution)
   1738 
   1739             self.missing_values = data.missing_values

/srv/scratch/lottep/anaconda3/envs/cellpymc2/lib/python3.7/site-packages/pymc3/model.py in as_tensor(data, name, model, distribution)
   1689         return data
   1690     else:
-> 1691         data = tt.as_tensor_variable(data, name=name)
   1692         data.missing_values = None
   1693         return data

/srv/scratch/lottep/anaconda3/envs/cellpymc2/lib/python3.7/site-packages/theano/tensor/basic.py in as_tensor_variable(x, name, ndim)
    156         if not isinstance(x.type, TensorType):
    157             raise AsTensorError(
--> 158                 "Variable type field must be a TensorType.", x, x.type)
    159 
    160         if ndim is None:

AsTensorError: ('Variable type field must be a TensorType.', SparseVariable{csr,int16}, Sparse[int16, csr])

I run the model on an ‘old’ titan X GPU, as newer GPU’s don’t support theano anymore. I installed the package yesterday, based on the environment.yml file provided, and then using the github as mentioned by you.

However, I encountered a problem with the arviz package. When loading the package in python, I received following error: module ‘arviz’ has no attribute ‘geweke’ For this reason, I installed arviz version 0.10.0 instead of 0.11.2. This made it possible to load the package into python. If necessary, I can send more information, but I just followed all provided steps.

[yozhikoff]

@onahman Setting GPU shouldn’t be too hard, we have a short guide about it here. The only potential issue is that it does require root access, is it a problem for you?