minor spelling tweaks

tensorflow/compiler/mlir/g3doc/tfl_ops.md

@@ -1217,7 +1217,7 @@ Softmax operator
 
 ### Description:
 
-Computes element-wise softmax activiations with the following formula
+Computes element-wise softmax activations with the following formula
 
   exp(input) / tf.reduce_sum(exp(input * beta), dim)
 

tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td

@@ -3033,7 +3033,7 @@ This op determines the maximum scale_factor that would map the initial
 quantized range.
 
 It determines the scale from one of input_min and input_max, then updates the
-other one to maximize the respresentable range.
+other one to maximize the representable range.
 
 e.g.
 

tensorflow/core/api_def/base_api/api_def_QuantizeAndDequantizeV2.pbtxt

@@ -103,7 +103,7 @@ This op determines the maximum scale_factor that would map the initial
 quantized range.
 
 It determines the scale from one of input_min and input_max, then updates the
-other one to maximize the respresentable range.
+other one to maximize the representable range.
 
 e.g.
 

tensorflow/core/profiler/g3doc/options.md

@@ -100,7 +100,7 @@ accelerator_micros and cpu_micros. Note: cpu and accelerator can run in parallel
 
 `-order_by`: Order the results by [name|depth|bytes|peak_bytes|residual_bytes|output_bytes|micros|accelerator_micros|cpu_micros|params|float_ops|occurrence]
 
-`-account_type_regexes`: Account and display the nodes whose types match one of the type regexes specified. tfprof allow user to define extra operation types for graph nodes through tensorflow.tfprof.OpLogProto proto. regexes are comma-sperated.
+`-account_type_regexes`: Account and display the nodes whose types match one of the type regexes specified. tfprof allow user to define extra operation types for graph nodes through tensorflow.tfprof.OpLogProto proto. regexes are comma-separated.
 
 `-start_name_regexes`: Show node starting from the node that matches the regexes, recursively. regexes are comma-separated.
 

tensorflow/core/profiler/g3doc/profile_model_architecture.md

@@ -63,7 +63,7 @@ For an operation to have float operation statistics:
     run_count.
 
 ```python
-# To profile float opertions in commandline, you need to pass --graph_path
+# To profile float operations in commandline, you need to pass --graph_path
 # and --op_log_path.
 tfprof> scope -min_float_ops 1 -select float_ops -account_displayed_op_only
 node name | # float_ops

tensorflow/go/op/wrappers.go

@@ -643,7 +643,7 @@ func QuantizeAndDequantizeV2NarrowRange(value bool) QuantizeAndDequantizeV2Attr
 // quantized range.
 //
 // It determines the scale from one of input_min and input_max, then updates the
-// other one to maximize the respresentable range.
+// other one to maximize the representable range.
 //
 // e.g.
 //

tensorflow/lite/experimental/examples/lstm/g3doc/README.md

@@ -316,7 +316,7 @@ def run_main(_):
       '--use_post_training_quantize',
       action='store_true',
       default=True,
-      help='Whether or not to use post_training_quatize.')
+      help='Whether or not to use post_training_quantize.')
   parsed_flags, _ = parser.parse_known_args()
   train_and_export(parsed_flags)
 

tensorflow/lite/experimental/micro/examples/micro_speech/apollo3/README.md

@@ -42,7 +42,7 @@
         *   cmsis_power.txt: the magnitude squared of the DFT
         *   cmsis_power_avg.txt: the 6-bin average of the magnitude squared of
             the DFT
-    *   Run both verisons of the 1KHz pre-processor test and then compare.
+    *   Run both versons of the 1KHz pre-processor test and then compare.
         *   These files can be plotted with "python compare\_1k.py"
     *   Also prints out the number of cycles the code took to execute (using the
         DWT->CYCCNT register)
@@ -60,7 +60,7 @@
         *   micro_power.txt: the magnitude squared of the DFT
         *   micro_power_avg.txt: the 6-bin average of the magnitude squared of
             the DFT
-    *   Run both verisons of the 1KHz pre-processor test and then compare.
+    *   Run both versons of the 1KHz pre-processor test and then compare.
         *   These files can be plotted with "python compare\_1k.py"
     *   Also prints out the number of cycles the code took to execute (using the
         DWT->CYCCNT register)
@@ -79,7 +79,7 @@
     is the same: a 1 kHz sinusoid.
 *   **get\_yesno\_data.cmd**: A GDB command file that runs preprocessor_test
     (where TARGET=apollo3evb) and dumps the calculated data for the "yes" and
-    "no" input wavfeorms to text files
+    "no" input waveforms to text files
 *   **\_main.c**: Point of entry for the micro_speech test
 *   **preprocessor_1k.cc**: A version of preprocessor.cc where a 1 kHz sinusoid
     is provided as input to the preprocessor

tensorflow/lite/experimental/micro/tools/make/targets/ecm3531/README.md

@@ -4,6 +4,6 @@ https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/experimenta
 CONTACT INFORMATION:
 
 Contact info@etacompute.com for more information on obtaining the Eta Compute
-SDK and evalution board.
+SDK and evaluation board.
 
 www.etacompute.com

tensorflow/lite/g3doc/models/image_classification/android.md

@@ -186,7 +186,7 @@ protected void runInference() {
 
 The output of the inference is stored in a byte array `labelProbArray`, which is
 allocated in the subclass's constructor. It consists of a single outer element,
-containing one innner element for each label in the classification model.
+containing one inner element for each label in the classification model.
 
 To run inference, we call `run()` on the interpreter instance, passing the input
 and output buffers as arguments.

tensorflow/lite/g3doc/performance/delegates.md

@@ -81,7 +81,7 @@ class MyDelegate {
 };
 
 // Create the TfLiteRegistration for the Kernel node which will replace
-// the subrgaph in the main TfLite graph.
+// the subgraph in the main TfLite graph.
 TfLiteRegistration GetMyDelegateNodeRegistration() {
   // This is the registration for the Delegate Node that gets added to
   // the TFLite graph instead of the subGraph it replaces.