From 705afa34fc4540593b6aa6dc6dd22ae02d41abea Mon Sep 17 00:00:00 2001 From: brett koonce Date: Sat, 17 Mar 2018 12:22:23 -0700 Subject: contrib: minor spelling tweaks (#17788) packages: model_pruning rnn solvers tensorrt --- tensorflow/contrib/model_pruning/python/layers/layers.py | 2 +- tensorflow/contrib/model_pruning/python/pruning.py | 2 +- tensorflow/contrib/rnn/ops/gru_ops.cc | 2 +- tensorflow/contrib/rnn/python/kernel_tests/lstm_ops_test.py | 2 +- tensorflow/contrib/rnn/python/ops/rnn_cell.py | 4 ++-- tensorflow/contrib/solvers/python/ops/least_squares.py | 2 +- tensorflow/contrib/solvers/python/ops/linear_equations.py | 2 +- tensorflow/contrib/tensorrt/convert/convert_graph.h | 2 +- tensorflow/contrib/tensorrt/convert/convert_nodes.cc | 8 ++++---- tensorflow/contrib/tensorrt/python/trt_convert.py | 2 +- tensorflow/contrib/tensorrt/resources/trt_int8_calibrator.cc | 2 +- tensorflow/contrib/tensorrt/test/test_tftrt.py | 2 +- 12 files changed, 16 insertions(+), 16 deletions(-) diff --git a/tensorflow/contrib/model_pruning/python/layers/layers.py b/tensorflow/contrib/model_pruning/python/layers/layers.py index 988748ad75..466daf204a 100644 --- a/tensorflow/contrib/model_pruning/python/layers/layers.py +++ b/tensorflow/contrib/model_pruning/python/layers/layers.py @@ -214,7 +214,7 @@ def masked_convolution(inputs, elif data_format == 'NCHW': df = 'channels_first' else: - raise ValueError('Unsupported data fromat', data_format) + raise ValueError('Unsupported data format', data_format) layer = layer_class( filters=num_outputs, diff --git a/tensorflow/contrib/model_pruning/python/pruning.py b/tensorflow/contrib/model_pruning/python/pruning.py index 86963be4b8..5146a4a2de 100644 --- a/tensorflow/contrib/model_pruning/python/pruning.py +++ b/tensorflow/contrib/model_pruning/python/pruning.py @@ -216,7 +216,7 @@ def _partitioned_variable_assign(partitioned_var, new_value): """Assign op for partitioned variables. Args: - partitioned_var: A partitioned tensotflow variable + partitioned_var: A partitioned tensorflow variable new_value: Value to be assigned to the variable var Returns: diff --git a/tensorflow/contrib/rnn/ops/gru_ops.cc b/tensorflow/contrib/rnn/ops/gru_ops.cc index e91d1e8a80..9c8e40851a 100644 --- a/tensorflow/contrib/rnn/ops/gru_ops.cc +++ b/tensorflow/contrib/rnn/ops/gru_ops.cc @@ -69,7 +69,7 @@ Element-wise dot product of a and b is represented by ab Element-wise dot product is represented by \circ Matrix multiplication is represented by * -Baises are initialized with : +Biases are initialized with : `b_ru` - constant_initializer(1.0) `b_c` - constant_initializer(0.0) diff --git a/tensorflow/contrib/rnn/python/kernel_tests/lstm_ops_test.py b/tensorflow/contrib/rnn/python/kernel_tests/lstm_ops_test.py index 7957edf68c..ffd2421894 100644 --- a/tensorflow/contrib/rnn/python/kernel_tests/lstm_ops_test.py +++ b/tensorflow/contrib/rnn/python/kernel_tests/lstm_ops_test.py @@ -54,7 +54,7 @@ def blocks_match(sess, use_peephole): initializer = init_ops.random_uniform_initializer(-0.01, 0.01, seed=19890212) with variable_scope.variable_scope("test", initializer=initializer): - # magic naming so that the cells pick up these variables and resuse them + # magic naming so that the cells pick up these variables and reuse them if use_peephole: wci = variable_scope.get_variable( "rnn/lstm_cell/w_i_diag", shape=[cell_size], dtype=dtypes.float32) diff --git a/tensorflow/contrib/rnn/python/ops/rnn_cell.py b/tensorflow/contrib/rnn/python/ops/rnn_cell.py index 358b2eb02b..2f6ae9f367 100644 --- a/tensorflow/contrib/rnn/python/ops/rnn_cell.py +++ b/tensorflow/contrib/rnn/python/ops/rnn_cell.py @@ -534,7 +534,7 @@ class GridLSTMCell(rnn_cell_impl.RNNCell): initializer: (optional) The initializer to use for the weight and projection matrices, default None. num_unit_shards: (optional) int, default 1, How to split the weight - matrix. If > 1,the weight matrix is stored across num_unit_shards. + matrix. If > 1, the weight matrix is stored across num_unit_shards. forget_bias: (optional) float, default 1.0, The initial bias of the forget gates, used to reduce the scale of forgetting at the beginning of the training. @@ -993,7 +993,7 @@ class BidirectionalGridLSTMCell(GridLSTMCell): initializer: (optional) The initializer to use for the weight and projection matrices, default None. num_unit_shards: (optional) int, default 1, How to split the weight - matrix. If > 1,the weight matrix is stored across num_unit_shards. + matrix. If > 1, the weight matrix is stored across num_unit_shards. forget_bias: (optional) float, default 1.0, The initial bias of the forget gates, used to reduce the scale of forgetting at the beginning of the training. diff --git a/tensorflow/contrib/solvers/python/ops/least_squares.py b/tensorflow/contrib/solvers/python/ops/least_squares.py index fb7c0eb649..6e164f5342 100644 --- a/tensorflow/contrib/solvers/python/ops/least_squares.py +++ b/tensorflow/contrib/solvers/python/ops/least_squares.py @@ -33,7 +33,7 @@ def cgls(operator, rhs, tol=1e-6, max_iter=20, name="cgls"): r"""Conjugate gradient least squares solver. Solves a linear least squares problem \\(||A x - rhs||_2\\) for a single - righ-hand side, using an iterative, matrix-free algorithm where the action of + right-hand side, using an iterative, matrix-free algorithm where the action of the matrix A is represented by `operator`. The CGLS algorithm implicitly applies the symmetric conjugate gradient algorithm to the normal equations \\(A^* A x = A^* rhs\\). The iteration terminates when either diff --git a/tensorflow/contrib/solvers/python/ops/linear_equations.py b/tensorflow/contrib/solvers/python/ops/linear_equations.py index d791d46763..9305c6a11c 100644 --- a/tensorflow/contrib/solvers/python/ops/linear_equations.py +++ b/tensorflow/contrib/solvers/python/ops/linear_equations.py @@ -41,7 +41,7 @@ def conjugate_gradient(operator, r"""Conjugate gradient solver. Solves a linear system of equations `A*x = rhs` for selfadjoint, positive - definite matrix `A` and righ-hand side vector `rhs`, using an iterative, + definite matrix `A` and right-hand side vector `rhs`, using an iterative, matrix-free algorithm where the action of the matrix A is represented by `operator`. The iteration terminates when either the number of iterations exceeds `max_iter` or when the residual norm has been reduced to `tol` diff --git a/tensorflow/contrib/tensorrt/convert/convert_graph.h b/tensorflow/contrib/tensorrt/convert/convert_graph.h index e1596e89e2..e01e4a5328 100644 --- a/tensorflow/contrib/tensorrt/convert/convert_graph.h +++ b/tensorflow/contrib/tensorrt/convert/convert_graph.h @@ -35,7 +35,7 @@ tensorflow::Status ConvertCalibGraphToInferGraph( // max_batch_size: maximum batch size which can be used for inference for // optimization targets inference run with max batch size. -// max_workspace_size_bytes: The upper bound of memory allowence for +// max_workspace_size_bytes: The upper bound of memory allowance for // engine building. tensorflow::Status ConvertGraphDefToTensorRT( const tensorflow::GraphDef& graph_def, diff --git a/tensorflow/contrib/tensorrt/convert/convert_nodes.cc b/tensorflow/contrib/tensorrt/convert/convert_nodes.cc index 75a3c3d034..92a692baa7 100644 --- a/tensorflow/contrib/tensorrt/convert/convert_nodes.cc +++ b/tensorflow/contrib/tensorrt/convert/convert_nodes.cc @@ -455,7 +455,7 @@ class Converter { if (trt_tensors_.count(name)) { inputs.push_back(trt_tensors_.at(name)); } else { - LOG(FATAL) << "input: " << name << " not availabled for node at, " + LOG(FATAL) << "input: " << name << " not available for node at, " << node_def.name(); } } @@ -884,7 +884,7 @@ tensorflow::Status BinaryTensorOpWeight( // default to element-wise auto scale_mode = nvinfer1::ScaleMode::kELEMENTWISE; - // TODO(jie): maybe use a permuatation instead to support more cases; + // TODO(jie): maybe use a permutation instead to support more cases; bool permutation_flag = false; if (weights.count() == 1) { @@ -1498,7 +1498,7 @@ tensorflow::Status ConvertConst(Converter& ctx, weights_tensor.int_val().begin(), weights_tensor.int_val() .end()); // make a local copy first to flatten - // doesn't have to be contigous + // doesn't have to be contiguous memcpy(dst, tensor_data.data(), len_tensor); // store into weight store weights = TRT_ShapedWeights(dtype, dst, scalar_shape); } @@ -2212,7 +2212,7 @@ tensorflow::Status InjectCalibrationNode(tensorrt::convert::SubGraphParams& s) { std::list order; for (tensorflow::Node* node : order_vec) { if (s.subgraph_node_ids.count(node->id())) { - order.push_front(node); // we want topological order to contstruct the + order.push_front(node); // we want topological order to construct the // network layer by layer } } diff --git a/tensorflow/contrib/tensorrt/python/trt_convert.py b/tensorflow/contrib/tensorrt/python/trt_convert.py index 666220d78c..338475d90e 100644 --- a/tensorflow/contrib/tensorrt/python/trt_convert.py +++ b/tensorflow/contrib/tensorrt/python/trt_convert.py @@ -41,7 +41,7 @@ def create_inference_graph(input_graph_def, max_workspace_size_bytes=2 << 20, precision_mode="FP32", minimum_segment_size=3): - """Python wrapper for the TRT transormation. + """Python wrapper for the TRT transformation. Args: input_graph_def: GraphDef object containing a model to be transformed. diff --git a/tensorflow/contrib/tensorrt/resources/trt_int8_calibrator.cc b/tensorflow/contrib/tensorrt/resources/trt_int8_calibrator.cc index 74df75902e..dc7c93f869 100644 --- a/tensorflow/contrib/tensorrt/resources/trt_int8_calibrator.cc +++ b/tensorflow/contrib/tensorrt/resources/trt_int8_calibrator.cc @@ -61,7 +61,7 @@ bool TRTInt8Calibrator::setBatch(const std::unordered_map& data, // TODO(aaroey): we should not use sync copy on default stream. Make sure // stream->ThenMemcpy() is used in future PRs. - // TODO(sami,aaroey): Need to figureout a way to ensure synchronization + // TODO(sami,aaroey): Need to figure out a way to ensure synchronization // between stream, perhaps using a tensor? auto status = cudaMemcpyAsync(d.first, it.second, d.second, cudaMemcpyDeviceToDevice, stream); diff --git a/tensorflow/contrib/tensorrt/test/test_tftrt.py b/tensorflow/contrib/tensorrt/test/test_tftrt.py index 0b661bd536..ad01bedd8f 100644 --- a/tensorflow/contrib/tensorrt/test/test_tftrt.py +++ b/tensorflow/contrib/tensorrt/test/test_tftrt.py @@ -75,7 +75,7 @@ def run_graph(gdef, dumm_inp): return val -# Use real data that is representatitive of the inference dataset +# Use real data that is representative of the inference dataset # for calibration. For this test script it is random data. def run_calibration(gdef, dumm_inp): """Run given calibration graph multiple times.""" -- cgit v1.2.3