Updated steps numbers from 13. 12 was duplicate

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Carlos Hernandez-Vaquero 2020-06-07 17:56:10 +02:00 committed by GitHub
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@ -301,7 +301,7 @@ successfully run.
TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, invoke_status); TF_LITE_MICRO_EXPECT_EQ(kTfLiteOk, invoke_status);
``` ```
### 12. Obtain the output ### 13. Obtain the output
The model's output tensor can be obtained by calling `output(0)` on the The model's output tensor can be obtained by calling `output(0)` on the
`tflite::MicroInterpreter`, where `0` represents the first (and only) output `tflite::MicroInterpreter`, where `0` represents the first (and only) output
@ -328,7 +328,7 @@ float value = output->data.f[0];
TF_LITE_MICRO_EXPECT_NEAR(0., value, 0.05); TF_LITE_MICRO_EXPECT_NEAR(0., value, 0.05);
``` ```
### 13. Run inference again ### 14. Run inference again
The remainder of the code runs inference several more times. In each instance, The remainder of the code runs inference several more times. In each instance,
we assign a value to the input tensor, invoke the interpreter, and read the we assign a value to the input tensor, invoke the interpreter, and read the
@ -351,7 +351,7 @@ value = output->data.f[0];
TF_LITE_MICRO_EXPECT_NEAR(-0.959, value, 0.05); TF_LITE_MICRO_EXPECT_NEAR(-0.959, value, 0.05);
``` ```
### 14. Read the application code ### 15. Read the application code
Once you have walked through this unit test, you should be able to understand Once you have walked through this unit test, you should be able to understand
the example's application code, located in the example's application code, located in