issue with medaka - Githubissues

Hi:

I installed decona and I get de racon results, however if I add the option -M it shows an error:

Filtering data... Data filtered with NanoFilt total raw sequences = 754 total filtered sequences = 483 Demultiplexing... Multi threading is not yet supported in epi2mme mode. Falling back to using a single thread. Adapters detected in 462 of 483 reads NBD104/NBD114 462: | ################### | 95.65 % none 21: | | 4.35 % Barcodes detected in 462 of 483 adapters barcode16 461: | ################### | 95.45 % barcode22 1: | | 0.21 % none 21: | | 4.35 % Demultiplexing finished in 0.67s Data demultiplexed, working directory changed to: /home/robertrm/03TEST/barcode16/demultiplexed_data Fastq reads are being transformed to fasta Transforming fastq to fasta Complete Clustering reads... Clustering barcode16/... Clustering barcode22/... Clustering complete. Aligning and making draft assembly of 315-1.fa... [M::mm_idx_gen::0.0020.00] collected minimizers [M::mm_idx_gen::0.0030.00] sorted minimizers [M::main::0.0030.00] loaded/built the index for 1 target sequence(s) [M::mm_mapopt_update::0.0040.00] mid_occ = 3 [M::mm_idx_stat] kmer size: 8; skip: 10; is_hpc: 0; #seq: 1 [M::mm_idx_stat::0.0050.00] distinct minimizers: 90 (98.89% are singletons); average occurrences: 1.011; average spacing: 5.791 [M::worker_pipeline::0.0154.30] mapped 315 sequences [M::main] Version: 2.17-r941 [M::main] CMD: minimap2 -ax map-ont -k8 -t 4 ref_315-1.fasta 315-1.fa [M::main] Real time: 0.016 sec; CPU: 0.062 sec; Peak RSS: 0.003 GB [racon::Polisher::initialize] loaded target sequences 0.001075 s [racon::Polisher::initialize] loaded sequences 0.001241 s [racon::Polisher::initialize] loaded overlaps 0.000870 s [racon::Polisher::initialize] aligning overlaps [====================] 0.004352 s [racon::Polisher::initialize] transformed data into windows 0.000348 s [racon::Polisher::polish] generated consensus 0.273021 s [racon::Polisher::] total = 0.282144 s Done Done polishing 315-1.fa Racon sequence with Medaka... Checking program versions This is medaka 1.1.2 Program Version Required Pass bcftools 1.10.2 1.9 True bgzip 1.10.2 1.9 True minimap2 2.17 2.11 True samtools 1.10 1.9 True tabix 1.10.2 1.9 True Aligning basecalls to draft Removing previous index file /home/robertrm/03TEST/barcode16/demultiplexed_data/barcode16/multi-seq/polished_315-1.fasta.mmi Removing previous index file /home/robertrm/03TEST/barcode16/demultiplexed_data/barcode16/multi-seq/polished_315-1.fasta.fai Constructing minimap index. [M::mm_idx_gen::0.0010.00] collected minimizers [M::mm_idx_gen::0.0020.00] sorted minimizers [M::main::0.0040.00] loaded/built the index for 1 target sequence(s) [M::mm_idx_stat] kmer size: 15; skip: 10; is_hpc: 0; #seq: 1 [M::mm_idx_stat::0.0040.00] distinct minimizers: 88 (100.00% are singletons); average occurrences: 1.000; average spacing: 6.068 [M::main] Version: 2.17-r941 [M::main] CMD: minimap2 -I 16G -x map-ont --MD -d /home/robertrm/03TEST/barcode16/demultiplexed_data/barcode16/multi-seq/polished_315-1.fasta.mmi /home/robertrm/03TEST/barcode16/demultiplexed_data/barcode16/multi-seq/polished_315-1.fasta [M::main] Real time: 0.006 sec; CPU: 0.000 sec; Peak RSS: 0.002 GB [M::main::0.0320.00] loaded/built the index for 1 target sequence(s) [M::mm_mapopt_update::0.0330.00] mid_occ = 2 [M::mm_idx_stat] kmer size: 15; skip: 10; is_hpc: 0; #seq: 1 [M::mm_idx_stat::0.0340.00] distinct minimizers: 88 (100.00% are singletons); average occurrences: 1.000; average spacing: 6.068 [M::worker_pipeline::0.0471.33] mapped 315 sequences [M::main] Version: 2.17-r941 [M::main] CMD: minimap2 -x map-ont --MD -t 4 -a -A 2 -B 4 -O 4,24 -E 2,1 /home/robertrm/03TEST/barcode16/demultiplexed_data/barcode16/multi-seq/polished_315-1.fasta.mmi /home/robertrm/03TEST/barcode16/demultiplexed_data/barcode16/multi-seq/315-1.fa [M::main] Real time: 0.051 sec; CPU: 0.062 sec; Peak RSS: 0.004 GB [bam_sort_core] merging from 0 files and 4 in-memory blocks... Running medaka consensus [18:37:20 - Predict] Processing region(s): 6721da47-6550-46d9-8d8f-3cbf44a89d34:0-534 [18:37:20 - Predict] Using model: /home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/medaka/data/r941_min_high_g360_model.hdf5. [18:37:20 - Predict] Setting tensorflow threads to 4. [18:37:20 - Predict] Processing 1 long region(s) with batching. [18:37:20 - ModelStore] filepath /home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/medaka/data/r941_min_high_g360_model.hdf5 [18:37:20 - ModelStore] ModelStore exception <class 'NotImplementedError'> Traceback (most recent call last): File "/home/robertrm/anaconda3/envs/decona/bin/medaka", line 11, in sys.exit(main()) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/medaka/medaka.py", line 669, in main args.func(args) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/medaka/prediction.py", line 136, in predict model = model_store.load_model(time_steps=args.chunk_len) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/medaka/datastore.py", line 77, in load_model model = model_partial_function(time_steps=time_steps) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/medaka/models.py", line 146, in build_model model.add(Bidirectional(gru, input_shape=input_shape)) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/training/tracking/base.py", line 517, in _method_wrapper result = method(self, args, kwargs) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/engine/sequential.py", line 208, in add layer(x) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/layers/wrappers.py", line 539, in call return super(Bidirectional, self).call(inputs, kwargs) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py", line 951, in call return self._functional_construction_call(inputs, args, kwargs, File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1090, in _functional_construction_call outputs = self._keras_tensor_symbolic_call( File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py", line 822, in _keras_tensor_symbolic_call return self._infer_output_signature(inputs, args, kwargs, input_masks) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py", line 863, in _infer_output_signature outputs = call_fn(inputs, args, kwargs) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/layers/wrappers.py", line 652, in call y = self.forward_layer(forward_inputs, File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/layers/recurrent.py", line 660, in call return super(RNN, self).call(inputs, kwargs) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1012, in call outputs = call_fn(inputs, *args, kwargs) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/layers/recurrent_v2.py", line 439, in call inputs, initialstate, = self._process_inputs(inputs, initial_state, None) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/layers/recurrent.py", line 859, in _process_inputs initial_state = self.get_initial_state(inputs) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/layers/recurrent.py", line 642, in get_initial_state init_state = get_initial_state_fn( File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/layers/recurrent.py", line 1948, in get_initial_state return _generate_zero_filled_state_for_cell(self, inputs, batch_size, dtype) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/layers/recurrent.py", line 2987, in _generate_zero_filled_state_for_cell return _generate_zero_filled_state(batch_size, cell.state_size, dtype) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/layers/recurrent.py", line 3005, in _generate_zero_filled_state return create_zeros(state_size) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/keras/layers/recurrent.py", line 3000, in create_zeros return array_ops.zeros(init_state_size, dtype=dtype) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py", line 201, in wrapper return target(*args, *kwargs) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/ops/array_ops.py", line 2819, in wrapped tensor = fun(args, kwargs) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/ops/array_ops.py", line 2868, in zeros output = _constant_if_small(zero, shape, dtype, name) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/ops/array_ops.py", line 2804, in _constant_if_small if np.prod(shape) < 1000: File "<__array_function__ internals>", line 180, in prod File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/numpy/core/fromnumeric.py", line 3045, in prod return _wrapreduction(a, np.multiply, 'prod', axis, dtype, out, File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/numpy/core/fromnumeric.py", line 86, in _wrapreduction return ufunc.reduce(obj, axis, dtype, out, **passkwargs) File "/home/robertrm/anaconda3/envs/decona/lib/python3.8/site-packages/tensorflow/python/framework/ops.py", line 852, in array raise NotImplementedError( NotImplementedError: Cannot convert a symbolic Tensor (bidirectional/forward_gru1/strided_slice:0) to a numpy array. This error may indicate that you're trying to pass a Tensor to a NumPy call, which is not supported Failed to run medaka consensus.

Any help wpuld be appreciated

Saskia-Oosterbroek / decona

issue with medaka #47