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Under the directory distributed-dp, I ran the command
distributed-dp
bazel run :fl_run -- \ --task=emnist_character \ --server_optimizer=sgd \ --server_learning_rate=1 \ --server_sgd_momentum=0.0 \ --client_optimizer=sgd \ --client_learning_rate=0.01 \ --client_sgd_momentum=0.9 \ --client_batch_size=20 \ --clients_per_round=100 \ --experiment_name=my_emnist_test \ --epsilon=6 \ --num_bits=20 \ --l2_norm_clip=1 \ --k_stddevs=3 \ --client_epochs_per_round=2 \ --dp_mechanism=dskellam \ --total_rounds=50 \ --logtostderr > log.txt 2>&1
In the log which I used to collect redirected messages, I obtained
Loading: Loading: 0 packages loaded DEBUG: Rule 'rules_python' indicated that a canonical reproducible form can be obtained by modifying arguments commit = "a0fbf98d4e3a232144df4d0d80b577c7a693b570", shallow_since = "1586444447 +0200" and dropping ["tag"] DEBUG: Repository rules_python instantiated at: /data/samuel/federated/WORKSPACE:5:15: in <toplevel> Repository rule git_repository defined at: /data/samuel/.cache/bazel/_bazel_zjiangaj/3fe67cea0bf4ee0dd0c8eb14b19e1272/external/bazel_tools/tools/build_defs/repo/git.bzl:199:33: in <toplevel> Analyzing: target //distributed_dp:fl_run (0 packages loaded, 0 targets configured) DEBUG: Rule 'rules_license' indicated that a canonical reproducible form can be obtained by modifying arguments commit = "e3bdc544ef373156da36638b774d65ff2d978bfa", shallow_since = "1667362800 -0400" and dropping ["tag"] DEBUG: Repository rules_license instantiated at: /data/samuel/federated/WORKSPACE:14:15: in <toplevel> Repository rule git_repository defined at: /data/samuel/.cache/bazel/_bazel_zjiangaj/3fe67cea0bf4ee0dd0c8eb14b19e1272/external/bazel_tools/tools/build_defs/repo/git.bzl:199:33: in <toplevel> INFO: Analyzed target //distributed_dp:fl_run (0 packages loaded, 0 targets configured). INFO: Found 1 target... [0 / 1] [Prepa] BazelWorkspaceStatusAction stable-status.txt Target //distributed_dp:fl_run up-to-date: bazel-bin/distributed_dp/fl_run INFO: Elapsed time: 4.312s, Critical Path: 0.02s INFO: 1 process: 1 internal. INFO: Build completed successfully, 1 total action INFO: Running command line: bazel-bin/distributed_dp/fl_run '--task=emnist_character' '--server_optimizer=sgd' '--server_learning_rate=1' '--server_sgd_momentum=0.0' '--client_optimizer=sgd' '--client_learning_rate=0.01' '--client_sgd_momentum=0.9' '--client_batch_size=20' '--clients_per_round=100' '--experiment_name=my_emnist_test' '--epsilon=6' '--num_bits=20' '--l2_norm_clip=1' '--k_stddevs=3' '--client_epochs_per_round=2' '--dp_mechanism=dskellam' '--total_rounds=50' --logtostderr INFO: Build completed successfully, 1 total action I0317 04:07:43.299935 140328278546240 sql_client_data.py:127] Loaded 3400 client ids from SQL database. I0317 04:07:50.917061 140328278546240 sql_client_data.py:127] Loaded 3400 client ids from SQL database. I0317 04:07:51.318575 140328278546240 keras_utils.py:362] Adding default num_examples metric to model I0317 04:07:51.318807 140328278546240 keras_utils.py:365] Adding default num_batches metric to model I0317 04:07:51.492904 140328278546240 keras_utils.py:362] Adding default num_examples metric to model I0317 04:07:51.493148 140328278546240 keras_utils.py:365] Adding default num_batches metric to model I0317 04:07:51.502441 140328278546240 fl_utils.py:72] Shared DP Parameters: I0317 04:07:51.502845 140328278546240 fl_utils.py:73] {'clip': 1.0, 'delta': 0.0002941176470588235, 'dim': 1018174, 'epsilon': 6.0, 'mechanism': 'dskellam', 'num_clients': 3400, 'num_clients_per_round': 100, 'num_rounds': 50, 'sampling_rate': 1.0} I0317 04:07:52.706335 140328278546240 fl_utils.py:152] dskellam parameters: I0317 04:07:52.706791 140328278546240 fl_utils.py:153] {'beta': 0.6065306597126334, 'bits': 20, 'dim': 1018174, 'gamma': 2.8479735556541443e-05, 'inflated_l2': 1.000120752105709, 'k_stddevs': 3, 'local_stddev': 0.49762363478987853, 'mechanism': 'dskellam', 'noise_mult_clip': 4.976236347898785, 'noise_mult_inflated': 4.975635529431367, 'padded_dim': 1048576.0, 'scale': 35112.68558005667} I0317 04:07:52.706896 140328278546240 ddpquery_utils.py:44] Conditional rounding set to True (beta = 0.606531) I0317 04:07:52.983747 140328278546240 keras_utils.py:362] Adding default num_examples metric to model I0317 04:07:52.983982 140328278546240 keras_utils.py:365] Adding default num_batches metric to model Traceback (most recent call last): File "/data/samuel/.cache/bazel/_bazel_zjiangaj/3fe67cea0bf4ee0dd0c8eb14b19e1272/execroot/org_federated_research/bazel-out/k8-opt/bin/distributed_dp/fl_run.runfiles/org_federated_research/distributed_dp/fl_run.py", line 304, in <module> app.run(main) File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/absl/app.py", line 312, in run _run_main(main, args) File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/absl/app.py", line 258, in _run_main sys.exit(main(argv)) File "/data/samuel/.cache/bazel/_bazel_zjiangaj/3fe67cea0bf4ee0dd0c8eb14b19e1272/execroot/org_federated_research/bazel-out/k8-opt/bin/distributed_dp/fl_run.runfiles/org_federated_research/distributed_dp/fl_run.py", line 246, in main iterative_process = tff.learning.algorithms.build_unweighted_fed_avg( File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/learning/algorithms/fed_avg.py", line 324, in build_unweighted_fed_avg return build_weighted_fed_avg( File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/learning/algorithms/fed_avg.py", line 198, in build_weighted_fed_avg aggregator = model_aggregator.create(model_update_type, File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/aggregators/factory_utils.py", line 52, in create aggregator = self._factory.create(value_type) File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/aggregators/mean.py", line 200, in create value_sum_process = self._value_sum_factory.create(value_type) File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/aggregators/robust.py", line 378, in create inner_agg_process = inner_agg_factory.create(value_type) File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/aggregators/differential_privacy.py", line 335, in create get_noised_result = computations.tf_computation( File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/core/impl/wrappers/computation_wrapper.py", line 496, in __call__ wrapped_func = self._strategy( File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/core/impl/wrappers/computation_wrapper.py", line 237, in __call__ return wrapped_fn_generator.send(result) File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/core/impl/wrappers/computation_wrapper.py", line 80, in _wrap_concrete concrete_fn = generator.send(result) File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/core/impl/wrappers/computation_wrapper_instances.py", line 63, in _tf_wrapper_fn comp_pb, extra_type_spec = tf_serializer.send(result) File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/core/impl/tensorflow_context/tensorflow_serialization.py", line 111, in tf_computation_serializer result_type, result_binding = tensorflow_utils.capture_result_from_graph( File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/core/impl/utils/tensorflow_utils.py", line 295, in capture_result_from_graph element_type_binding_pairs = [ File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/core/impl/utils/tensorflow_utils.py", line 296, in <listcomp> capture_result_from_graph(e, graph) for e in result File "/data/samuel/anaconda3/envs/google/lib/python3.9/site-packages/tensorflow_federated/python/core/impl/utils/tensorflow_utils.py", line 328, in capture_result_from_graph raise UnsupportedGraphResultError( tensorflow_federated.python.core.impl.utils.tensorflow_utils.UnsupportedGraphResultError: Cannot capture a result of an unsupported type NoneType.
By the way, I am using Python 3.9.7, with pip installed packages (only ones related to tensorflow is listed)
tensorboard 2.8.0 tensorboard-data-server 0.6.1 tensorboard-plugin-wit 1.8.1 tensorflow 2.8.4 tensorflow-addons 0.19.0 tensorflow-datasets 4.5.2 tensorflow-estimator 2.8.0 tensorflow-federated 0.24.0 tensorflow-io-gcs-filesystem 0.31.0 tensorflow-metadata 1.12.0 tensorflow-model-optimization 0.7.3 tensorflow-privacy 0.8.0 tensorflow-probability 0.15.0
Could anyone help me with this issue, if you can successfully run the above command? Thank you in advance.
The text was updated successfully, but these errors were encountered:
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Under the directory
distributed-dp, I ran the commandbazel run :fl_run -- \ --task=emnist_character \ --server_optimizer=sgd \ --server_learning_rate=1 \ --server_sgd_momentum=0.0 \ --client_optimizer=sgd \ --client_learning_rate=0.01 \ --client_sgd_momentum=0.9 \ --client_batch_size=20 \ --clients_per_round=100 \ --experiment_name=my_emnist_test \ --epsilon=6 \ --num_bits=20 \ --l2_norm_clip=1 \ --k_stddevs=3 \ --client_epochs_per_round=2 \ --dp_mechanism=dskellam \ --total_rounds=50 \ --logtostderr > log.txt 2>&1In the log which I used to collect redirected messages, I obtained
By the way, I am using Python 3.9.7, with pip installed packages (only ones related to tensorflow is listed)
Could anyone help me with this issue, if you can successfully run the above command? Thank you in advance.
The text was updated successfully, but these errors were encountered: