From 516ad32e454e80231e547deac827558f3d2e0ab9 Mon Sep 17 00:00:00 2001
From: LiamSwayne <108629034+LiamSwayne@users.noreply.github.com>
Date: Fri, 9 Jun 2023 08:25:43 -0700
Subject: [PATCH] (documentation) grammatical fixes in trial-evaluation.md
 (#1652)

Summary:
The changes made are grammatical and do not affect the ideas communicated in the file.

Pull Request resolved: https://github.com/facebook/Ax/pull/1652

Reviewed By: bernardbeckerman

Differential Revision: D46581530

Pulled By: Balandat

fbshipit-source-id: 928601c8259d3c7417079ff2cb4e219cdf386d3c
---
 docs/trial-evaluation.md | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/docs/trial-evaluation.md b/docs/trial-evaluation.md
index c1ad0cbc262..38b0d1e2a5b 100644
--- a/docs/trial-evaluation.md
+++ b/docs/trial-evaluation.md
@@ -34,16 +34,16 @@ For example, this evaluation function computes mean and SEM for [Hartmann6](http
 from ax.utils.measurement.synthetic_functions import hartmann6
 def hartmann_evaluation_function(parameterization):
     x = np.array([parameterization.get(f"x{i+1}") for i in range(6)])
-    # Standard error is 0, since we are computing a synthetic function.
+    # Standard error is 0 since we are computing a synthetic function.
     return {"hartmann6": (hartmann6(x), 0.0), "l2norm": (np.sqrt((x ** 2).sum()), 0.0)}
 ```
 
-This function computes just the objective mean and SEM, assuming the [Branin](https://www.sfu.ca/~ssurjano/branin.html) function is the objective on the experiment:
+This function computes just the objective mean and SEM, assuming the [Branin](https://www.sfu.ca/~ssurjano/branin.html) function is the objective of the experiment:
 
 ```python
 from ax.utils.measurement.synthetic_functions import branin
 def branin_evaluation_function(parameterization):
-    # Standard error is 0, since we are computing a synthetic function.
+    # Standard error is 0 since we are computing a synthetic function.
     return (branin(parameterization.get("x1"), parameterization.get("x2")), 0.0)
 ```
 
@@ -69,7 +69,7 @@ It can also accept a `weight` parameter, a nullable `float` representing the fra
 
 The Developer API is supported by the [```Experiment```](/api/core.html#module-ax.core.experiment) class. In this paradigm, the user specifies:
   * [`Runner`](../api/core.html#ax.core.runner.Runner): Defines how to deploy the experiment.
-  * List of [`Metrics`](../api/core.html#ax.core.metric.Metric): Each defining how to compute/fetch data for a given objective or outcome.
+  * List of [`Metrics`](../api/core.html#ax.core.metric.Metric): Each defines how to compute/fetch data for a given objective or outcome.
 
 The experiment requires a `generator_run` to create a new trial or batch trial.  A generator run can be generated by a model.  The trial then has its own `run` and `mark_complete` methods.
 ```python
@@ -90,7 +90,7 @@ for i in range(15):
 
 ### Custom Metrics
 
-Similar to trial evaluation in the Service API, a custom metric computes a mean and SEM for each arm of a trial.  However, the metric's `fetch_trial_data` method will be called automatically by the experiment's [```fetch_data```](/api/core.html#ax.core.base_trial.BaseTrial.fetch_data) method.  If there are multiple objetives or outcomes that need to be optimized for, each needs its own metric.
+Similar to a trial evaluation in the Service API, a custom metric computes a mean and SEM for each arm of a trial.  However, the metric's `fetch_trial_data` method will be called automatically by the experiment's [```fetch_data```](/api/core.html#ax.core.base_trial.BaseTrial.fetch_data) method.  If there are multiple objectives or outcomes that need to be optimized for, each needs its own metric.
 
 ```python
 class MyMetric(Metric):